gagan3012 commited on
Commit
fbe1a40
1 Parent(s): 7d7a901

Upload folder using huggingface_hub

Browse files
README.md ADDED
@@ -0,0 +1,55 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language:
3
+ - en
4
+ license: apache-2.0
5
+ tags:
6
+ - mistral
7
+ - Eclipse-13B-dpo
8
+ pipeline_tag: text-generation
9
+ ---
10
+ # Model Card for Eclipse-13B-dpo
11
+
12
+ Mistral-7B-v0.1 model fine-tuned on the Ultrafeedback dataset using techinques shown in the paper [Self-Rewarding Language Models](https://arxiv.org/abs/2401.10020).
13
+
14
+ ## Instruction format
15
+
16
+ In order to leverage instruction fine-tuning, your prompt should be surrounded by `[INST]` and `[/INST]` tokens. The very first instruction should begin with a begin of sentence id. The next instructions should not. The assistant generation will be ended by the end-of-sentence token id.
17
+
18
+ E.g.
19
+ ```
20
+ text = "<s>[INST] What is your favourite condiment? [/INST]"
21
+ "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!</s> "
22
+ "[INST] Do you have mayonnaise recipes? [/INST]"
23
+ ```
24
+
25
+ This format is available as a [chat template](https://huggingface.co/docs/transformers/main/chat_templating) via the `apply_chat_template()` method:
26
+
27
+ ```python
28
+ from transformers import AutoModelForCausalLM, AutoTokenizer
29
+
30
+ device = "cuda" # the device to load the model onto
31
+
32
+ model = AutoModelForCausalLM.from_pretrained("Xenon1/Eclipse-13B-dpo")
33
+ tokenizer = AutoTokenizer.from_pretrained("Xenon1/Eclipse-13B-dpo")
34
+
35
+ messages = [
36
+ {"role": "user", "content": "What is your favourite condiment?"},
37
+ {"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"},
38
+ {"role": "user", "content": "Do you have mayonnaise recipes?"}
39
+ ]
40
+
41
+ encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")
42
+
43
+ model_inputs = encodeds.to(device)
44
+ model.to(device)
45
+
46
+ generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
47
+ decoded = tokenizer.batch_decode(generated_ids)
48
+ print(decoded[0])
49
+ ```
50
+
51
+ ## Model Architecture
52
+ This instruction model is based on Mistral-7B-v0.1, a transformer model with the following architecture choices:
53
+ - Grouped-Query Attention
54
+ - Sliding-Window Attention
55
+ - Byte-fallback BPE tokenizer
checkpoint-500/README.md ADDED
@@ -0,0 +1,204 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: /lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Eclipse
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+
201
+
202
+ ### Framework versions
203
+
204
+ - PEFT 0.7.2.dev0
checkpoint-500/adapter_config.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Eclipse",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "loftq_config": {},
12
+ "lora_alpha": 16,
13
+ "lora_dropout": 0.05,
14
+ "megatron_config": null,
15
+ "megatron_core": "megatron.core",
16
+ "modules_to_save": null,
17
+ "peft_type": "LORA",
18
+ "r": 16,
19
+ "rank_pattern": {},
20
+ "revision": null,
21
+ "target_modules": [
22
+ "v_proj",
23
+ "gate",
24
+ "w3",
25
+ "o_proj",
26
+ "w2",
27
+ "q_proj",
28
+ "k_proj",
29
+ "w1"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_rslora": false
33
+ }
checkpoint-500/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:313ae8e488fc32bc10279b537426e795382546b8e1bd8e147b223b1352d4eec7
3
+ size 144806848
checkpoint-500/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8c410b043cec69414944ad9aaba136a274d369eff3543d1d2a2bb7f6d4e38597
3
+ size 579246546
checkpoint-500/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1ff264f99d31b522cc7e2a4eac9d38606d0c58a34c0adc74d71e0ca8b371dc36
3
+ size 14244
checkpoint-500/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c083f48f7f724546d361cb36491230bf2dd9c0b2adbb44f2eb0b8b46955eb901
3
+ size 1064
checkpoint-500/special_tokens_map.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<unk>",
4
+ "<s>",
5
+ "</s>"
6
+ ],
7
+ "bos_token": {
8
+ "content": "<s>",
9
+ "lstrip": false,
10
+ "normalized": false,
11
+ "rstrip": false,
12
+ "single_word": false
13
+ },
14
+ "eos_token": {
15
+ "content": "</s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false
20
+ },
21
+ "pad_token": "</s>",
22
+ "unk_token": {
23
+ "content": "<unk>",
24
+ "lstrip": false,
25
+ "normalized": false,
26
+ "rstrip": false,
27
+ "single_word": false
28
+ }
29
+ }
checkpoint-500/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-500/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
3
+ size 493443
checkpoint-500/tokenizer_config.json ADDED
@@ -0,0 +1,50 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<unk>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<s>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "</s>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ }
29
+ },
30
+ "additional_special_tokens": [
31
+ "<unk>",
32
+ "<s>",
33
+ "</s>"
34
+ ],
35
+ "bos_token": "<s>",
36
+ "clean_up_tokenization_spaces": false,
37
+ "eos_token": "</s>",
38
+ "legacy": true,
39
+ "max_length": null,
40
+ "model_max_length": 255,
41
+ "pad_to_multiple_of": null,
42
+ "pad_token": "</s>",
43
+ "pad_token_type_id": 0,
44
+ "padding_side": "left",
45
+ "sp_model_kwargs": {},
46
+ "spaces_between_special_tokens": false,
47
+ "tokenizer_class": "LlamaTokenizer",
48
+ "unk_token": "<unk>",
49
+ "use_default_system_prompt": true
50
+ }
checkpoint-500/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-500/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d52826c05375787a6ebde06e94a33a9bec79624a18b3acf1a9a8f8d382abacde
3
+ size 4728
config.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Eclipse",
3
+ "architectures": [
4
+ "MixtralForCausalLM"
5
+ ],
6
+ "attention_dropout": 0.0,
7
+ "bos_token_id": 1,
8
+ "eos_token_id": 2,
9
+ "hidden_act": "silu",
10
+ "hidden_size": 4096,
11
+ "initializer_range": 0.02,
12
+ "intermediate_size": 14336,
13
+ "max_position_embeddings": 32768,
14
+ "model_type": "mixtral",
15
+ "num_attention_heads": 32,
16
+ "num_experts_per_tok": 2,
17
+ "num_hidden_layers": 32,
18
+ "num_key_value_heads": 8,
19
+ "num_local_experts": 2,
20
+ "output_router_logits": false,
21
+ "pad_token_id": 2,
22
+ "rms_norm_eps": 1e-05,
23
+ "rope_theta": 10000.0,
24
+ "router_aux_loss_coef": 0.001,
25
+ "sliding_window": null,
26
+ "tie_word_embeddings": false,
27
+ "torch_dtype": "float16",
28
+ "transformers_version": "4.37.1",
29
+ "unsloth_version": "2024.1",
30
+ "use_cache": true,
31
+ "vocab_size": 32000
32
+ }
final_checkpoint/README.md ADDED
@@ -0,0 +1,204 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: /lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Eclipse
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+
201
+
202
+ ### Framework versions
203
+
204
+ - PEFT 0.7.2.dev0
final_checkpoint/adapter_config.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Eclipse",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "loftq_config": {},
12
+ "lora_alpha": 16,
13
+ "lora_dropout": 0.05,
14
+ "megatron_config": null,
15
+ "megatron_core": "megatron.core",
16
+ "modules_to_save": null,
17
+ "peft_type": "LORA",
18
+ "r": 16,
19
+ "rank_pattern": {},
20
+ "revision": null,
21
+ "target_modules": [
22
+ "v_proj",
23
+ "gate",
24
+ "w3",
25
+ "o_proj",
26
+ "w2",
27
+ "q_proj",
28
+ "k_proj",
29
+ "w1"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_rslora": false
33
+ }
final_checkpoint/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aafb61da9b2cf957b3f4301c7a0d0382e72ac4017c464b19578abf0638252a8f
3
+ size 144806848
final_checkpoint/special_tokens_map.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<unk>",
4
+ "<s>",
5
+ "</s>"
6
+ ],
7
+ "bos_token": {
8
+ "content": "<s>",
9
+ "lstrip": false,
10
+ "normalized": false,
11
+ "rstrip": false,
12
+ "single_word": false
13
+ },
14
+ "eos_token": {
15
+ "content": "</s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false
20
+ },
21
+ "pad_token": "</s>",
22
+ "unk_token": {
23
+ "content": "<unk>",
24
+ "lstrip": false,
25
+ "normalized": false,
26
+ "rstrip": false,
27
+ "single_word": false
28
+ }
29
+ }
final_checkpoint/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
final_checkpoint/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
3
+ size 493443
final_checkpoint/tokenizer_config.json ADDED
@@ -0,0 +1,50 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<unk>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<s>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "</s>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ }
29
+ },
30
+ "additional_special_tokens": [
31
+ "<unk>",
32
+ "<s>",
33
+ "</s>"
34
+ ],
35
+ "bos_token": "<s>",
36
+ "clean_up_tokenization_spaces": false,
37
+ "eos_token": "</s>",
38
+ "legacy": true,
39
+ "max_length": null,
40
+ "model_max_length": 255,
41
+ "pad_to_multiple_of": null,
42
+ "pad_token": "</s>",
43
+ "pad_token_type_id": 0,
44
+ "padding_side": "left",
45
+ "sp_model_kwargs": {},
46
+ "spaces_between_special_tokens": false,
47
+ "tokenizer_class": "LlamaTokenizer",
48
+ "unk_token": "<unk>",
49
+ "use_default_system_prompt": true
50
+ }
generation_config.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "bos_token_id": 1,
4
+ "eos_token_id": 2,
5
+ "pad_token_id": 2,
6
+ "transformers_version": "4.37.1"
7
+ }
model-00001-of-00006.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:43286d16ec6a6671a09d9518653f304cade6d34738a635860b42668c9b6a5879
3
+ size 4993525184
model-00002-of-00006.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:afa49f358984cfa6233911755191cfcadfd83f836170cce9a089ad5a55091fad
3
+ size 4932724792
model-00003-of-00006.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b8b3d1201682c0ad0e86c2da3ae124076d245f41f7122972e69f0f835f715b46
3
+ size 4966262448
model-00004-of-00006.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:001491f74c5ebe0700e905e843a952af1cf4ff76c11db59eb1c8e41afe41f0f7
3
+ size 4966262448
model-00005-of-00006.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:67800f76b58c6b316dd994518f4a328cc2bbb26e52bd1e211d633da5dc7af11a
3
+ size 4932741456
model-00006-of-00006.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e0875f779911c723308e3a315579f9bb5b77c28bb0b783cdafc532f98afcc13c
3
+ size 966812864
model.safetensors.index.json ADDED
@@ -0,0 +1,426 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metadata": {
3
+ "total_size": 25758277632
4
+ },
5
+ "weight_map": {
6
+ "lm_head.weight": "model-00006-of-00006.safetensors",
7
+ "model.embed_tokens.weight": "model-00001-of-00006.safetensors",
8
+ "model.layers.0.block_sparse_moe.experts.0.w1.weight": "model-00001-of-00006.safetensors",
9
+ "model.layers.0.block_sparse_moe.experts.0.w2.weight": "model-00001-of-00006.safetensors",
10
+ "model.layers.0.block_sparse_moe.experts.0.w3.weight": "model-00001-of-00006.safetensors",
11
+ "model.layers.0.block_sparse_moe.experts.1.w1.weight": "model-00001-of-00006.safetensors",
12
+ "model.layers.0.block_sparse_moe.experts.1.w2.weight": "model-00001-of-00006.safetensors",
13
+ "model.layers.0.block_sparse_moe.experts.1.w3.weight": "model-00001-of-00006.safetensors",
14
+ "model.layers.0.block_sparse_moe.gate.weight": "model-00001-of-00006.safetensors",
15
+ "model.layers.0.input_layernorm.weight": "model-00001-of-00006.safetensors",
16
+ "model.layers.0.post_attention_layernorm.weight": "model-00001-of-00006.safetensors",
17
+ "model.layers.0.self_attn.k_proj.weight": "model-00001-of-00006.safetensors",
18
+ "model.layers.0.self_attn.o_proj.weight": "model-00001-of-00006.safetensors",
19
+ "model.layers.0.self_attn.q_proj.weight": "model-00001-of-00006.safetensors",
20
+ "model.layers.0.self_attn.v_proj.weight": "model-00001-of-00006.safetensors",
21
+ "model.layers.1.block_sparse_moe.experts.0.w1.weight": "model-00001-of-00006.safetensors",
22
+ "model.layers.1.block_sparse_moe.experts.0.w2.weight": "model-00001-of-00006.safetensors",
23
+ "model.layers.1.block_sparse_moe.experts.0.w3.weight": "model-00001-of-00006.safetensors",
24
+ "model.layers.1.block_sparse_moe.experts.1.w1.weight": "model-00001-of-00006.safetensors",
25
+ "model.layers.1.block_sparse_moe.experts.1.w2.weight": "model-00001-of-00006.safetensors",
26
+ "model.layers.1.block_sparse_moe.experts.1.w3.weight": "model-00001-of-00006.safetensors",
27
+ "model.layers.1.block_sparse_moe.gate.weight": "model-00001-of-00006.safetensors",
28
+ "model.layers.1.input_layernorm.weight": "model-00001-of-00006.safetensors",
29
+ "model.layers.1.post_attention_layernorm.weight": "model-00001-of-00006.safetensors",
30
+ "model.layers.1.self_attn.k_proj.weight": "model-00001-of-00006.safetensors",
31
+ "model.layers.1.self_attn.o_proj.weight": "model-00001-of-00006.safetensors",
32
+ "model.layers.1.self_attn.q_proj.weight": "model-00001-of-00006.safetensors",
33
+ "model.layers.1.self_attn.v_proj.weight": "model-00001-of-00006.safetensors",
34
+ "model.layers.10.block_sparse_moe.experts.0.w1.weight": "model-00002-of-00006.safetensors",
35
+ "model.layers.10.block_sparse_moe.experts.0.w2.weight": "model-00002-of-00006.safetensors",
36
+ "model.layers.10.block_sparse_moe.experts.0.w3.weight": "model-00002-of-00006.safetensors",
37
+ "model.layers.10.block_sparse_moe.experts.1.w1.weight": "model-00002-of-00006.safetensors",
38
+ "model.layers.10.block_sparse_moe.experts.1.w2.weight": "model-00002-of-00006.safetensors",
39
+ "model.layers.10.block_sparse_moe.experts.1.w3.weight": "model-00002-of-00006.safetensors",
40
+ "model.layers.10.block_sparse_moe.gate.weight": "model-00002-of-00006.safetensors",
41
+ "model.layers.10.input_layernorm.weight": "model-00002-of-00006.safetensors",
42
+ "model.layers.10.post_attention_layernorm.weight": "model-00002-of-00006.safetensors",
43
+ "model.layers.10.self_attn.k_proj.weight": "model-00002-of-00006.safetensors",
44
+ "model.layers.10.self_attn.o_proj.weight": "model-00002-of-00006.safetensors",
45
+ "model.layers.10.self_attn.q_proj.weight": "model-00002-of-00006.safetensors",
46
+ "model.layers.10.self_attn.v_proj.weight": "model-00002-of-00006.safetensors",
47
+ "model.layers.11.block_sparse_moe.experts.0.w1.weight": "model-00002-of-00006.safetensors",
48
+ "model.layers.11.block_sparse_moe.experts.0.w2.weight": "model-00002-of-00006.safetensors",
49
+ "model.layers.11.block_sparse_moe.experts.0.w3.weight": "model-00002-of-00006.safetensors",
50
+ "model.layers.11.block_sparse_moe.experts.1.w1.weight": "model-00002-of-00006.safetensors",
51
+ "model.layers.11.block_sparse_moe.experts.1.w2.weight": "model-00002-of-00006.safetensors",
52
+ "model.layers.11.block_sparse_moe.experts.1.w3.weight": "model-00002-of-00006.safetensors",
53
+ "model.layers.11.block_sparse_moe.gate.weight": "model-00002-of-00006.safetensors",
54
+ "model.layers.11.input_layernorm.weight": "model-00002-of-00006.safetensors",
55
+ "model.layers.11.post_attention_layernorm.weight": "model-00002-of-00006.safetensors",
56
+ "model.layers.11.self_attn.k_proj.weight": "model-00002-of-00006.safetensors",
57
+ "model.layers.11.self_attn.o_proj.weight": "model-00002-of-00006.safetensors",
58
+ "model.layers.11.self_attn.q_proj.weight": "model-00002-of-00006.safetensors",
59
+ "model.layers.11.self_attn.v_proj.weight": "model-00002-of-00006.safetensors",
60
+ "model.layers.12.block_sparse_moe.experts.0.w1.weight": "model-00002-of-00006.safetensors",
61
+ "model.layers.12.block_sparse_moe.experts.0.w2.weight": "model-00003-of-00006.safetensors",
62
+ "model.layers.12.block_sparse_moe.experts.0.w3.weight": "model-00003-of-00006.safetensors",
63
+ "model.layers.12.block_sparse_moe.experts.1.w1.weight": "model-00003-of-00006.safetensors",
64
+ "model.layers.12.block_sparse_moe.experts.1.w2.weight": "model-00003-of-00006.safetensors",
65
+ "model.layers.12.block_sparse_moe.experts.1.w3.weight": "model-00003-of-00006.safetensors",
66
+ "model.layers.12.block_sparse_moe.gate.weight": "model-00002-of-00006.safetensors",
67
+ "model.layers.12.input_layernorm.weight": "model-00003-of-00006.safetensors",
68
+ "model.layers.12.post_attention_layernorm.weight": "model-00003-of-00006.safetensors",
69
+ "model.layers.12.self_attn.k_proj.weight": "model-00002-of-00006.safetensors",
70
+ "model.layers.12.self_attn.o_proj.weight": "model-00002-of-00006.safetensors",
71
+ "model.layers.12.self_attn.q_proj.weight": "model-00002-of-00006.safetensors",
72
+ "model.layers.12.self_attn.v_proj.weight": "model-00002-of-00006.safetensors",
73
+ "model.layers.13.block_sparse_moe.experts.0.w1.weight": "model-00003-of-00006.safetensors",
74
+ "model.layers.13.block_sparse_moe.experts.0.w2.weight": "model-00003-of-00006.safetensors",
75
+ "model.layers.13.block_sparse_moe.experts.0.w3.weight": "model-00003-of-00006.safetensors",
76
+ "model.layers.13.block_sparse_moe.experts.1.w1.weight": "model-00003-of-00006.safetensors",
77
+ "model.layers.13.block_sparse_moe.experts.1.w2.weight": "model-00003-of-00006.safetensors",
78
+ "model.layers.13.block_sparse_moe.experts.1.w3.weight": "model-00003-of-00006.safetensors",
79
+ "model.layers.13.block_sparse_moe.gate.weight": "model-00003-of-00006.safetensors",
80
+ "model.layers.13.input_layernorm.weight": "model-00003-of-00006.safetensors",
81
+ "model.layers.13.post_attention_layernorm.weight": "model-00003-of-00006.safetensors",
82
+ "model.layers.13.self_attn.k_proj.weight": "model-00003-of-00006.safetensors",
83
+ "model.layers.13.self_attn.o_proj.weight": "model-00003-of-00006.safetensors",
84
+ "model.layers.13.self_attn.q_proj.weight": "model-00003-of-00006.safetensors",
85
+ "model.layers.13.self_attn.v_proj.weight": "model-00003-of-00006.safetensors",
86
+ "model.layers.14.block_sparse_moe.experts.0.w1.weight": "model-00003-of-00006.safetensors",
87
+ "model.layers.14.block_sparse_moe.experts.0.w2.weight": "model-00003-of-00006.safetensors",
88
+ "model.layers.14.block_sparse_moe.experts.0.w3.weight": "model-00003-of-00006.safetensors",
89
+ "model.layers.14.block_sparse_moe.experts.1.w1.weight": "model-00003-of-00006.safetensors",
90
+ "model.layers.14.block_sparse_moe.experts.1.w2.weight": "model-00003-of-00006.safetensors",
91
+ "model.layers.14.block_sparse_moe.experts.1.w3.weight": "model-00003-of-00006.safetensors",
92
+ "model.layers.14.block_sparse_moe.gate.weight": "model-00003-of-00006.safetensors",
93
+ "model.layers.14.input_layernorm.weight": "model-00003-of-00006.safetensors",
94
+ "model.layers.14.post_attention_layernorm.weight": "model-00003-of-00006.safetensors",
95
+ "model.layers.14.self_attn.k_proj.weight": "model-00003-of-00006.safetensors",
96
+ "model.layers.14.self_attn.o_proj.weight": "model-00003-of-00006.safetensors",
97
+ "model.layers.14.self_attn.q_proj.weight": "model-00003-of-00006.safetensors",
98
+ "model.layers.14.self_attn.v_proj.weight": "model-00003-of-00006.safetensors",
99
+ "model.layers.15.block_sparse_moe.experts.0.w1.weight": "model-00003-of-00006.safetensors",
100
+ "model.layers.15.block_sparse_moe.experts.0.w2.weight": "model-00003-of-00006.safetensors",
101
+ "model.layers.15.block_sparse_moe.experts.0.w3.weight": "model-00003-of-00006.safetensors",
102
+ "model.layers.15.block_sparse_moe.experts.1.w1.weight": "model-00003-of-00006.safetensors",
103
+ "model.layers.15.block_sparse_moe.experts.1.w2.weight": "model-00003-of-00006.safetensors",
104
+ "model.layers.15.block_sparse_moe.experts.1.w3.weight": "model-00003-of-00006.safetensors",
105
+ "model.layers.15.block_sparse_moe.gate.weight": "model-00003-of-00006.safetensors",
106
+ "model.layers.15.input_layernorm.weight": "model-00003-of-00006.safetensors",
107
+ "model.layers.15.post_attention_layernorm.weight": "model-00003-of-00006.safetensors",
108
+ "model.layers.15.self_attn.k_proj.weight": "model-00003-of-00006.safetensors",
109
+ "model.layers.15.self_attn.o_proj.weight": "model-00003-of-00006.safetensors",
110
+ "model.layers.15.self_attn.q_proj.weight": "model-00003-of-00006.safetensors",
111
+ "model.layers.15.self_attn.v_proj.weight": "model-00003-of-00006.safetensors",
112
+ "model.layers.16.block_sparse_moe.experts.0.w1.weight": "model-00003-of-00006.safetensors",
113
+ "model.layers.16.block_sparse_moe.experts.0.w2.weight": "model-00003-of-00006.safetensors",
114
+ "model.layers.16.block_sparse_moe.experts.0.w3.weight": "model-00003-of-00006.safetensors",
115
+ "model.layers.16.block_sparse_moe.experts.1.w1.weight": "model-00003-of-00006.safetensors",
116
+ "model.layers.16.block_sparse_moe.experts.1.w2.weight": "model-00003-of-00006.safetensors",
117
+ "model.layers.16.block_sparse_moe.experts.1.w3.weight": "model-00003-of-00006.safetensors",
118
+ "model.layers.16.block_sparse_moe.gate.weight": "model-00003-of-00006.safetensors",
119
+ "model.layers.16.input_layernorm.weight": "model-00003-of-00006.safetensors",
120
+ "model.layers.16.post_attention_layernorm.weight": "model-00003-of-00006.safetensors",
121
+ "model.layers.16.self_attn.k_proj.weight": "model-00003-of-00006.safetensors",
122
+ "model.layers.16.self_attn.o_proj.weight": "model-00003-of-00006.safetensors",
123
+ "model.layers.16.self_attn.q_proj.weight": "model-00003-of-00006.safetensors",
124
+ "model.layers.16.self_attn.v_proj.weight": "model-00003-of-00006.safetensors",
125
+ "model.layers.17.block_sparse_moe.experts.0.w1.weight": "model-00003-of-00006.safetensors",
126
+ "model.layers.17.block_sparse_moe.experts.0.w2.weight": "model-00003-of-00006.safetensors",
127
+ "model.layers.17.block_sparse_moe.experts.0.w3.weight": "model-00003-of-00006.safetensors",
128
+ "model.layers.17.block_sparse_moe.experts.1.w1.weight": "model-00003-of-00006.safetensors",
129
+ "model.layers.17.block_sparse_moe.experts.1.w2.weight": "model-00003-of-00006.safetensors",
130
+ "model.layers.17.block_sparse_moe.experts.1.w3.weight": "model-00003-of-00006.safetensors",
131
+ "model.layers.17.block_sparse_moe.gate.weight": "model-00003-of-00006.safetensors",
132
+ "model.layers.17.input_layernorm.weight": "model-00003-of-00006.safetensors",
133
+ "model.layers.17.post_attention_layernorm.weight": "model-00003-of-00006.safetensors",
134
+ "model.layers.17.self_attn.k_proj.weight": "model-00003-of-00006.safetensors",
135
+ "model.layers.17.self_attn.o_proj.weight": "model-00003-of-00006.safetensors",
136
+ "model.layers.17.self_attn.q_proj.weight": "model-00003-of-00006.safetensors",
137
+ "model.layers.17.self_attn.v_proj.weight": "model-00003-of-00006.safetensors",
138
+ "model.layers.18.block_sparse_moe.experts.0.w1.weight": "model-00003-of-00006.safetensors",
139
+ "model.layers.18.block_sparse_moe.experts.0.w2.weight": "model-00003-of-00006.safetensors",
140
+ "model.layers.18.block_sparse_moe.experts.0.w3.weight": "model-00003-of-00006.safetensors",
141
+ "model.layers.18.block_sparse_moe.experts.1.w1.weight": "model-00004-of-00006.safetensors",
142
+ "model.layers.18.block_sparse_moe.experts.1.w2.weight": "model-00004-of-00006.safetensors",
143
+ "model.layers.18.block_sparse_moe.experts.1.w3.weight": "model-00004-of-00006.safetensors",
144
+ "model.layers.18.block_sparse_moe.gate.weight": "model-00003-of-00006.safetensors",
145
+ "model.layers.18.input_layernorm.weight": "model-00004-of-00006.safetensors",
146
+ "model.layers.18.post_attention_layernorm.weight": "model-00004-of-00006.safetensors",
147
+ "model.layers.18.self_attn.k_proj.weight": "model-00003-of-00006.safetensors",
148
+ "model.layers.18.self_attn.o_proj.weight": "model-00003-of-00006.safetensors",
149
+ "model.layers.18.self_attn.q_proj.weight": "model-00003-of-00006.safetensors",
150
+ "model.layers.18.self_attn.v_proj.weight": "model-00003-of-00006.safetensors",
151
+ "model.layers.19.block_sparse_moe.experts.0.w1.weight": "model-00004-of-00006.safetensors",
152
+ "model.layers.19.block_sparse_moe.experts.0.w2.weight": "model-00004-of-00006.safetensors",
153
+ "model.layers.19.block_sparse_moe.experts.0.w3.weight": "model-00004-of-00006.safetensors",
154
+ "model.layers.19.block_sparse_moe.experts.1.w1.weight": "model-00004-of-00006.safetensors",
155
+ "model.layers.19.block_sparse_moe.experts.1.w2.weight": "model-00004-of-00006.safetensors",
156
+ "model.layers.19.block_sparse_moe.experts.1.w3.weight": "model-00004-of-00006.safetensors",
157
+ "model.layers.19.block_sparse_moe.gate.weight": "model-00004-of-00006.safetensors",
158
+ "model.layers.19.input_layernorm.weight": "model-00004-of-00006.safetensors",
159
+ "model.layers.19.post_attention_layernorm.weight": "model-00004-of-00006.safetensors",
160
+ "model.layers.19.self_attn.k_proj.weight": "model-00004-of-00006.safetensors",
161
+ "model.layers.19.self_attn.o_proj.weight": "model-00004-of-00006.safetensors",
162
+ "model.layers.19.self_attn.q_proj.weight": "model-00004-of-00006.safetensors",
163
+ "model.layers.19.self_attn.v_proj.weight": "model-00004-of-00006.safetensors",
164
+ "model.layers.2.block_sparse_moe.experts.0.w1.weight": "model-00001-of-00006.safetensors",
165
+ "model.layers.2.block_sparse_moe.experts.0.w2.weight": "model-00001-of-00006.safetensors",
166
+ "model.layers.2.block_sparse_moe.experts.0.w3.weight": "model-00001-of-00006.safetensors",
167
+ "model.layers.2.block_sparse_moe.experts.1.w1.weight": "model-00001-of-00006.safetensors",
168
+ "model.layers.2.block_sparse_moe.experts.1.w2.weight": "model-00001-of-00006.safetensors",
169
+ "model.layers.2.block_sparse_moe.experts.1.w3.weight": "model-00001-of-00006.safetensors",
170
+ "model.layers.2.block_sparse_moe.gate.weight": "model-00001-of-00006.safetensors",
171
+ "model.layers.2.input_layernorm.weight": "model-00001-of-00006.safetensors",
172
+ "model.layers.2.post_attention_layernorm.weight": "model-00001-of-00006.safetensors",
173
+ "model.layers.2.self_attn.k_proj.weight": "model-00001-of-00006.safetensors",
174
+ "model.layers.2.self_attn.o_proj.weight": "model-00001-of-00006.safetensors",
175
+ "model.layers.2.self_attn.q_proj.weight": "model-00001-of-00006.safetensors",
176
+ "model.layers.2.self_attn.v_proj.weight": "model-00001-of-00006.safetensors",
177
+ "model.layers.20.block_sparse_moe.experts.0.w1.weight": "model-00004-of-00006.safetensors",
178
+ "model.layers.20.block_sparse_moe.experts.0.w2.weight": "model-00004-of-00006.safetensors",
179
+ "model.layers.20.block_sparse_moe.experts.0.w3.weight": "model-00004-of-00006.safetensors",
180
+ "model.layers.20.block_sparse_moe.experts.1.w1.weight": "model-00004-of-00006.safetensors",
181
+ "model.layers.20.block_sparse_moe.experts.1.w2.weight": "model-00004-of-00006.safetensors",
182
+ "model.layers.20.block_sparse_moe.experts.1.w3.weight": "model-00004-of-00006.safetensors",
183
+ "model.layers.20.block_sparse_moe.gate.weight": "model-00004-of-00006.safetensors",
184
+ "model.layers.20.input_layernorm.weight": "model-00004-of-00006.safetensors",
185
+ "model.layers.20.post_attention_layernorm.weight": "model-00004-of-00006.safetensors",
186
+ "model.layers.20.self_attn.k_proj.weight": "model-00004-of-00006.safetensors",
187
+ "model.layers.20.self_attn.o_proj.weight": "model-00004-of-00006.safetensors",
188
+ "model.layers.20.self_attn.q_proj.weight": "model-00004-of-00006.safetensors",
189
+ "model.layers.20.self_attn.v_proj.weight": "model-00004-of-00006.safetensors",
190
+ "model.layers.21.block_sparse_moe.experts.0.w1.weight": "model-00004-of-00006.safetensors",
191
+ "model.layers.21.block_sparse_moe.experts.0.w2.weight": "model-00004-of-00006.safetensors",
192
+ "model.layers.21.block_sparse_moe.experts.0.w3.weight": "model-00004-of-00006.safetensors",
193
+ "model.layers.21.block_sparse_moe.experts.1.w1.weight": "model-00004-of-00006.safetensors",
194
+ "model.layers.21.block_sparse_moe.experts.1.w2.weight": "model-00004-of-00006.safetensors",
195
+ "model.layers.21.block_sparse_moe.experts.1.w3.weight": "model-00004-of-00006.safetensors",
196
+ "model.layers.21.block_sparse_moe.gate.weight": "model-00004-of-00006.safetensors",
197
+ "model.layers.21.input_layernorm.weight": "model-00004-of-00006.safetensors",
198
+ "model.layers.21.post_attention_layernorm.weight": "model-00004-of-00006.safetensors",
199
+ "model.layers.21.self_attn.k_proj.weight": "model-00004-of-00006.safetensors",
200
+ "model.layers.21.self_attn.o_proj.weight": "model-00004-of-00006.safetensors",
201
+ "model.layers.21.self_attn.q_proj.weight": "model-00004-of-00006.safetensors",
202
+ "model.layers.21.self_attn.v_proj.weight": "model-00004-of-00006.safetensors",
203
+ "model.layers.22.block_sparse_moe.experts.0.w1.weight": "model-00004-of-00006.safetensors",
204
+ "model.layers.22.block_sparse_moe.experts.0.w2.weight": "model-00004-of-00006.safetensors",
205
+ "model.layers.22.block_sparse_moe.experts.0.w3.weight": "model-00004-of-00006.safetensors",
206
+ "model.layers.22.block_sparse_moe.experts.1.w1.weight": "model-00004-of-00006.safetensors",
207
+ "model.layers.22.block_sparse_moe.experts.1.w2.weight": "model-00004-of-00006.safetensors",
208
+ "model.layers.22.block_sparse_moe.experts.1.w3.weight": "model-00004-of-00006.safetensors",
209
+ "model.layers.22.block_sparse_moe.gate.weight": "model-00004-of-00006.safetensors",
210
+ "model.layers.22.input_layernorm.weight": "model-00004-of-00006.safetensors",
211
+ "model.layers.22.post_attention_layernorm.weight": "model-00004-of-00006.safetensors",
212
+ "model.layers.22.self_attn.k_proj.weight": "model-00004-of-00006.safetensors",
213
+ "model.layers.22.self_attn.o_proj.weight": "model-00004-of-00006.safetensors",
214
+ "model.layers.22.self_attn.q_proj.weight": "model-00004-of-00006.safetensors",
215
+ "model.layers.22.self_attn.v_proj.weight": "model-00004-of-00006.safetensors",
216
+ "model.layers.23.block_sparse_moe.experts.0.w1.weight": "model-00004-of-00006.safetensors",
217
+ "model.layers.23.block_sparse_moe.experts.0.w2.weight": "model-00004-of-00006.safetensors",
218
+ "model.layers.23.block_sparse_moe.experts.0.w3.weight": "model-00004-of-00006.safetensors",
219
+ "model.layers.23.block_sparse_moe.experts.1.w1.weight": "model-00004-of-00006.safetensors",
220
+ "model.layers.23.block_sparse_moe.experts.1.w2.weight": "model-00004-of-00006.safetensors",
221
+ "model.layers.23.block_sparse_moe.experts.1.w3.weight": "model-00004-of-00006.safetensors",
222
+ "model.layers.23.block_sparse_moe.gate.weight": "model-00004-of-00006.safetensors",
223
+ "model.layers.23.input_layernorm.weight": "model-00004-of-00006.safetensors",
224
+ "model.layers.23.post_attention_layernorm.weight": "model-00004-of-00006.safetensors",
225
+ "model.layers.23.self_attn.k_proj.weight": "model-00004-of-00006.safetensors",
226
+ "model.layers.23.self_attn.o_proj.weight": "model-00004-of-00006.safetensors",
227
+ "model.layers.23.self_attn.q_proj.weight": "model-00004-of-00006.safetensors",
228
+ "model.layers.23.self_attn.v_proj.weight": "model-00004-of-00006.safetensors",
229
+ "model.layers.24.block_sparse_moe.experts.0.w1.weight": "model-00004-of-00006.safetensors",
230
+ "model.layers.24.block_sparse_moe.experts.0.w2.weight": "model-00004-of-00006.safetensors",
231
+ "model.layers.24.block_sparse_moe.experts.0.w3.weight": "model-00004-of-00006.safetensors",
232
+ "model.layers.24.block_sparse_moe.experts.1.w1.weight": "model-00004-of-00006.safetensors",
233
+ "model.layers.24.block_sparse_moe.experts.1.w2.weight": "model-00004-of-00006.safetensors",
234
+ "model.layers.24.block_sparse_moe.experts.1.w3.weight": "model-00005-of-00006.safetensors",
235
+ "model.layers.24.block_sparse_moe.gate.weight": "model-00004-of-00006.safetensors",
236
+ "model.layers.24.input_layernorm.weight": "model-00005-of-00006.safetensors",
237
+ "model.layers.24.post_attention_layernorm.weight": "model-00005-of-00006.safetensors",
238
+ "model.layers.24.self_attn.k_proj.weight": "model-00004-of-00006.safetensors",
239
+ "model.layers.24.self_attn.o_proj.weight": "model-00004-of-00006.safetensors",
240
+ "model.layers.24.self_attn.q_proj.weight": "model-00004-of-00006.safetensors",
241
+ "model.layers.24.self_attn.v_proj.weight": "model-00004-of-00006.safetensors",
242
+ "model.layers.25.block_sparse_moe.experts.0.w1.weight": "model-00005-of-00006.safetensors",
243
+ "model.layers.25.block_sparse_moe.experts.0.w2.weight": "model-00005-of-00006.safetensors",
244
+ "model.layers.25.block_sparse_moe.experts.0.w3.weight": "model-00005-of-00006.safetensors",
245
+ "model.layers.25.block_sparse_moe.experts.1.w1.weight": "model-00005-of-00006.safetensors",
246
+ "model.layers.25.block_sparse_moe.experts.1.w2.weight": "model-00005-of-00006.safetensors",
247
+ "model.layers.25.block_sparse_moe.experts.1.w3.weight": "model-00005-of-00006.safetensors",
248
+ "model.layers.25.block_sparse_moe.gate.weight": "model-00005-of-00006.safetensors",
249
+ "model.layers.25.input_layernorm.weight": "model-00005-of-00006.safetensors",
250
+ "model.layers.25.post_attention_layernorm.weight": "model-00005-of-00006.safetensors",
251
+ "model.layers.25.self_attn.k_proj.weight": "model-00005-of-00006.safetensors",
252
+ "model.layers.25.self_attn.o_proj.weight": "model-00005-of-00006.safetensors",
253
+ "model.layers.25.self_attn.q_proj.weight": "model-00005-of-00006.safetensors",
254
+ "model.layers.25.self_attn.v_proj.weight": "model-00005-of-00006.safetensors",
255
+ "model.layers.26.block_sparse_moe.experts.0.w1.weight": "model-00005-of-00006.safetensors",
256
+ "model.layers.26.block_sparse_moe.experts.0.w2.weight": "model-00005-of-00006.safetensors",
257
+ "model.layers.26.block_sparse_moe.experts.0.w3.weight": "model-00005-of-00006.safetensors",
258
+ "model.layers.26.block_sparse_moe.experts.1.w1.weight": "model-00005-of-00006.safetensors",
259
+ "model.layers.26.block_sparse_moe.experts.1.w2.weight": "model-00005-of-00006.safetensors",
260
+ "model.layers.26.block_sparse_moe.experts.1.w3.weight": "model-00005-of-00006.safetensors",
261
+ "model.layers.26.block_sparse_moe.gate.weight": "model-00005-of-00006.safetensors",
262
+ "model.layers.26.input_layernorm.weight": "model-00005-of-00006.safetensors",
263
+ "model.layers.26.post_attention_layernorm.weight": "model-00005-of-00006.safetensors",
264
+ "model.layers.26.self_attn.k_proj.weight": "model-00005-of-00006.safetensors",
265
+ "model.layers.26.self_attn.o_proj.weight": "model-00005-of-00006.safetensors",
266
+ "model.layers.26.self_attn.q_proj.weight": "model-00005-of-00006.safetensors",
267
+ "model.layers.26.self_attn.v_proj.weight": "model-00005-of-00006.safetensors",
268
+ "model.layers.27.block_sparse_moe.experts.0.w1.weight": "model-00005-of-00006.safetensors",
269
+ "model.layers.27.block_sparse_moe.experts.0.w2.weight": "model-00005-of-00006.safetensors",
270
+ "model.layers.27.block_sparse_moe.experts.0.w3.weight": "model-00005-of-00006.safetensors",
271
+ "model.layers.27.block_sparse_moe.experts.1.w1.weight": "model-00005-of-00006.safetensors",
272
+ "model.layers.27.block_sparse_moe.experts.1.w2.weight": "model-00005-of-00006.safetensors",
273
+ "model.layers.27.block_sparse_moe.experts.1.w3.weight": "model-00005-of-00006.safetensors",
274
+ "model.layers.27.block_sparse_moe.gate.weight": "model-00005-of-00006.safetensors",
275
+ "model.layers.27.input_layernorm.weight": "model-00005-of-00006.safetensors",
276
+ "model.layers.27.post_attention_layernorm.weight": "model-00005-of-00006.safetensors",
277
+ "model.layers.27.self_attn.k_proj.weight": "model-00005-of-00006.safetensors",
278
+ "model.layers.27.self_attn.o_proj.weight": "model-00005-of-00006.safetensors",
279
+ "model.layers.27.self_attn.q_proj.weight": "model-00005-of-00006.safetensors",
280
+ "model.layers.27.self_attn.v_proj.weight": "model-00005-of-00006.safetensors",
281
+ "model.layers.28.block_sparse_moe.experts.0.w1.weight": "model-00005-of-00006.safetensors",
282
+ "model.layers.28.block_sparse_moe.experts.0.w2.weight": "model-00005-of-00006.safetensors",
283
+ "model.layers.28.block_sparse_moe.experts.0.w3.weight": "model-00005-of-00006.safetensors",
284
+ "model.layers.28.block_sparse_moe.experts.1.w1.weight": "model-00005-of-00006.safetensors",
285
+ "model.layers.28.block_sparse_moe.experts.1.w2.weight": "model-00005-of-00006.safetensors",
286
+ "model.layers.28.block_sparse_moe.experts.1.w3.weight": "model-00005-of-00006.safetensors",
287
+ "model.layers.28.block_sparse_moe.gate.weight": "model-00005-of-00006.safetensors",
288
+ "model.layers.28.input_layernorm.weight": "model-00005-of-00006.safetensors",
289
+ "model.layers.28.post_attention_layernorm.weight": "model-00005-of-00006.safetensors",
290
+ "model.layers.28.self_attn.k_proj.weight": "model-00005-of-00006.safetensors",
291
+ "model.layers.28.self_attn.o_proj.weight": "model-00005-of-00006.safetensors",
292
+ "model.layers.28.self_attn.q_proj.weight": "model-00005-of-00006.safetensors",
293
+ "model.layers.28.self_attn.v_proj.weight": "model-00005-of-00006.safetensors",
294
+ "model.layers.29.block_sparse_moe.experts.0.w1.weight": "model-00005-of-00006.safetensors",
295
+ "model.layers.29.block_sparse_moe.experts.0.w2.weight": "model-00005-of-00006.safetensors",
296
+ "model.layers.29.block_sparse_moe.experts.0.w3.weight": "model-00005-of-00006.safetensors",
297
+ "model.layers.29.block_sparse_moe.experts.1.w1.weight": "model-00005-of-00006.safetensors",
298
+ "model.layers.29.block_sparse_moe.experts.1.w2.weight": "model-00005-of-00006.safetensors",
299
+ "model.layers.29.block_sparse_moe.experts.1.w3.weight": "model-00005-of-00006.safetensors",
300
+ "model.layers.29.block_sparse_moe.gate.weight": "model-00005-of-00006.safetensors",
301
+ "model.layers.29.input_layernorm.weight": "model-00005-of-00006.safetensors",
302
+ "model.layers.29.post_attention_layernorm.weight": "model-00005-of-00006.safetensors",
303
+ "model.layers.29.self_attn.k_proj.weight": "model-00005-of-00006.safetensors",
304
+ "model.layers.29.self_attn.o_proj.weight": "model-00005-of-00006.safetensors",
305
+ "model.layers.29.self_attn.q_proj.weight": "model-00005-of-00006.safetensors",
306
+ "model.layers.29.self_attn.v_proj.weight": "model-00005-of-00006.safetensors",
307
+ "model.layers.3.block_sparse_moe.experts.0.w1.weight": "model-00001-of-00006.safetensors",
308
+ "model.layers.3.block_sparse_moe.experts.0.w2.weight": "model-00001-of-00006.safetensors",
309
+ "model.layers.3.block_sparse_moe.experts.0.w3.weight": "model-00001-of-00006.safetensors",
310
+ "model.layers.3.block_sparse_moe.experts.1.w1.weight": "model-00001-of-00006.safetensors",
311
+ "model.layers.3.block_sparse_moe.experts.1.w2.weight": "model-00001-of-00006.safetensors",
312
+ "model.layers.3.block_sparse_moe.experts.1.w3.weight": "model-00001-of-00006.safetensors",
313
+ "model.layers.3.block_sparse_moe.gate.weight": "model-00001-of-00006.safetensors",
314
+ "model.layers.3.input_layernorm.weight": "model-00001-of-00006.safetensors",
315
+ "model.layers.3.post_attention_layernorm.weight": "model-00001-of-00006.safetensors",
316
+ "model.layers.3.self_attn.k_proj.weight": "model-00001-of-00006.safetensors",
317
+ "model.layers.3.self_attn.o_proj.weight": "model-00001-of-00006.safetensors",
318
+ "model.layers.3.self_attn.q_proj.weight": "model-00001-of-00006.safetensors",
319
+ "model.layers.3.self_attn.v_proj.weight": "model-00001-of-00006.safetensors",
320
+ "model.layers.30.block_sparse_moe.experts.0.w1.weight": "model-00005-of-00006.safetensors",
321
+ "model.layers.30.block_sparse_moe.experts.0.w2.weight": "model-00005-of-00006.safetensors",
322
+ "model.layers.30.block_sparse_moe.experts.0.w3.weight": "model-00005-of-00006.safetensors",
323
+ "model.layers.30.block_sparse_moe.experts.1.w1.weight": "model-00005-of-00006.safetensors",
324
+ "model.layers.30.block_sparse_moe.experts.1.w2.weight": "model-00005-of-00006.safetensors",
325
+ "model.layers.30.block_sparse_moe.experts.1.w3.weight": "model-00005-of-00006.safetensors",
326
+ "model.layers.30.block_sparse_moe.gate.weight": "model-00005-of-00006.safetensors",
327
+ "model.layers.30.input_layernorm.weight": "model-00005-of-00006.safetensors",
328
+ "model.layers.30.post_attention_layernorm.weight": "model-00005-of-00006.safetensors",
329
+ "model.layers.30.self_attn.k_proj.weight": "model-00005-of-00006.safetensors",
330
+ "model.layers.30.self_attn.o_proj.weight": "model-00005-of-00006.safetensors",
331
+ "model.layers.30.self_attn.q_proj.weight": "model-00005-of-00006.safetensors",
332
+ "model.layers.30.self_attn.v_proj.weight": "model-00005-of-00006.safetensors",
333
+ "model.layers.31.block_sparse_moe.experts.0.w1.weight": "model-00006-of-00006.safetensors",
334
+ "model.layers.31.block_sparse_moe.experts.0.w2.weight": "model-00006-of-00006.safetensors",
335
+ "model.layers.31.block_sparse_moe.experts.0.w3.weight": "model-00006-of-00006.safetensors",
336
+ "model.layers.31.block_sparse_moe.experts.1.w1.weight": "model-00006-of-00006.safetensors",
337
+ "model.layers.31.block_sparse_moe.experts.1.w2.weight": "model-00006-of-00006.safetensors",
338
+ "model.layers.31.block_sparse_moe.experts.1.w3.weight": "model-00006-of-00006.safetensors",
339
+ "model.layers.31.block_sparse_moe.gate.weight": "model-00005-of-00006.safetensors",
340
+ "model.layers.31.input_layernorm.weight": "model-00006-of-00006.safetensors",
341
+ "model.layers.31.post_attention_layernorm.weight": "model-00006-of-00006.safetensors",
342
+ "model.layers.31.self_attn.k_proj.weight": "model-00005-of-00006.safetensors",
343
+ "model.layers.31.self_attn.o_proj.weight": "model-00005-of-00006.safetensors",
344
+ "model.layers.31.self_attn.q_proj.weight": "model-00005-of-00006.safetensors",
345
+ "model.layers.31.self_attn.v_proj.weight": "model-00005-of-00006.safetensors",
346
+ "model.layers.4.block_sparse_moe.experts.0.w1.weight": "model-00001-of-00006.safetensors",
347
+ "model.layers.4.block_sparse_moe.experts.0.w2.weight": "model-00001-of-00006.safetensors",
348
+ "model.layers.4.block_sparse_moe.experts.0.w3.weight": "model-00001-of-00006.safetensors",
349
+ "model.layers.4.block_sparse_moe.experts.1.w1.weight": "model-00001-of-00006.safetensors",
350
+ "model.layers.4.block_sparse_moe.experts.1.w2.weight": "model-00001-of-00006.safetensors",
351
+ "model.layers.4.block_sparse_moe.experts.1.w3.weight": "model-00001-of-00006.safetensors",
352
+ "model.layers.4.block_sparse_moe.gate.weight": "model-00001-of-00006.safetensors",
353
+ "model.layers.4.input_layernorm.weight": "model-00001-of-00006.safetensors",
354
+ "model.layers.4.post_attention_layernorm.weight": "model-00001-of-00006.safetensors",
355
+ "model.layers.4.self_attn.k_proj.weight": "model-00001-of-00006.safetensors",
356
+ "model.layers.4.self_attn.o_proj.weight": "model-00001-of-00006.safetensors",
357
+ "model.layers.4.self_attn.q_proj.weight": "model-00001-of-00006.safetensors",
358
+ "model.layers.4.self_attn.v_proj.weight": "model-00001-of-00006.safetensors",
359
+ "model.layers.5.block_sparse_moe.experts.0.w1.weight": "model-00001-of-00006.safetensors",
360
+ "model.layers.5.block_sparse_moe.experts.0.w2.weight": "model-00001-of-00006.safetensors",
361
+ "model.layers.5.block_sparse_moe.experts.0.w3.weight": "model-00001-of-00006.safetensors",
362
+ "model.layers.5.block_sparse_moe.experts.1.w1.weight": "model-00001-of-00006.safetensors",
363
+ "model.layers.5.block_sparse_moe.experts.1.w2.weight": "model-00001-of-00006.safetensors",
364
+ "model.layers.5.block_sparse_moe.experts.1.w3.weight": "model-00001-of-00006.safetensors",
365
+ "model.layers.5.block_sparse_moe.gate.weight": "model-00001-of-00006.safetensors",
366
+ "model.layers.5.input_layernorm.weight": "model-00001-of-00006.safetensors",
367
+ "model.layers.5.post_attention_layernorm.weight": "model-00001-of-00006.safetensors",
368
+ "model.layers.5.self_attn.k_proj.weight": "model-00001-of-00006.safetensors",
369
+ "model.layers.5.self_attn.o_proj.weight": "model-00001-of-00006.safetensors",
370
+ "model.layers.5.self_attn.q_proj.weight": "model-00001-of-00006.safetensors",
371
+ "model.layers.5.self_attn.v_proj.weight": "model-00001-of-00006.safetensors",
372
+ "model.layers.6.block_sparse_moe.experts.0.w1.weight": "model-00002-of-00006.safetensors",
373
+ "model.layers.6.block_sparse_moe.experts.0.w2.weight": "model-00002-of-00006.safetensors",
374
+ "model.layers.6.block_sparse_moe.experts.0.w3.weight": "model-00002-of-00006.safetensors",
375
+ "model.layers.6.block_sparse_moe.experts.1.w1.weight": "model-00002-of-00006.safetensors",
376
+ "model.layers.6.block_sparse_moe.experts.1.w2.weight": "model-00002-of-00006.safetensors",
377
+ "model.layers.6.block_sparse_moe.experts.1.w3.weight": "model-00002-of-00006.safetensors",
378
+ "model.layers.6.block_sparse_moe.gate.weight": "model-00002-of-00006.safetensors",
379
+ "model.layers.6.input_layernorm.weight": "model-00002-of-00006.safetensors",
380
+ "model.layers.6.post_attention_layernorm.weight": "model-00002-of-00006.safetensors",
381
+ "model.layers.6.self_attn.k_proj.weight": "model-00002-of-00006.safetensors",
382
+ "model.layers.6.self_attn.o_proj.weight": "model-00002-of-00006.safetensors",
383
+ "model.layers.6.self_attn.q_proj.weight": "model-00002-of-00006.safetensors",
384
+ "model.layers.6.self_attn.v_proj.weight": "model-00002-of-00006.safetensors",
385
+ "model.layers.7.block_sparse_moe.experts.0.w1.weight": "model-00002-of-00006.safetensors",
386
+ "model.layers.7.block_sparse_moe.experts.0.w2.weight": "model-00002-of-00006.safetensors",
387
+ "model.layers.7.block_sparse_moe.experts.0.w3.weight": "model-00002-of-00006.safetensors",
388
+ "model.layers.7.block_sparse_moe.experts.1.w1.weight": "model-00002-of-00006.safetensors",
389
+ "model.layers.7.block_sparse_moe.experts.1.w2.weight": "model-00002-of-00006.safetensors",
390
+ "model.layers.7.block_sparse_moe.experts.1.w3.weight": "model-00002-of-00006.safetensors",
391
+ "model.layers.7.block_sparse_moe.gate.weight": "model-00002-of-00006.safetensors",
392
+ "model.layers.7.input_layernorm.weight": "model-00002-of-00006.safetensors",
393
+ "model.layers.7.post_attention_layernorm.weight": "model-00002-of-00006.safetensors",
394
+ "model.layers.7.self_attn.k_proj.weight": "model-00002-of-00006.safetensors",
395
+ "model.layers.7.self_attn.o_proj.weight": "model-00002-of-00006.safetensors",
396
+ "model.layers.7.self_attn.q_proj.weight": "model-00002-of-00006.safetensors",
397
+ "model.layers.7.self_attn.v_proj.weight": "model-00002-of-00006.safetensors",
398
+ "model.layers.8.block_sparse_moe.experts.0.w1.weight": "model-00002-of-00006.safetensors",
399
+ "model.layers.8.block_sparse_moe.experts.0.w2.weight": "model-00002-of-00006.safetensors",
400
+ "model.layers.8.block_sparse_moe.experts.0.w3.weight": "model-00002-of-00006.safetensors",
401
+ "model.layers.8.block_sparse_moe.experts.1.w1.weight": "model-00002-of-00006.safetensors",
402
+ "model.layers.8.block_sparse_moe.experts.1.w2.weight": "model-00002-of-00006.safetensors",
403
+ "model.layers.8.block_sparse_moe.experts.1.w3.weight": "model-00002-of-00006.safetensors",
404
+ "model.layers.8.block_sparse_moe.gate.weight": "model-00002-of-00006.safetensors",
405
+ "model.layers.8.input_layernorm.weight": "model-00002-of-00006.safetensors",
406
+ "model.layers.8.post_attention_layernorm.weight": "model-00002-of-00006.safetensors",
407
+ "model.layers.8.self_attn.k_proj.weight": "model-00002-of-00006.safetensors",
408
+ "model.layers.8.self_attn.o_proj.weight": "model-00002-of-00006.safetensors",
409
+ "model.layers.8.self_attn.q_proj.weight": "model-00002-of-00006.safetensors",
410
+ "model.layers.8.self_attn.v_proj.weight": "model-00002-of-00006.safetensors",
411
+ "model.layers.9.block_sparse_moe.experts.0.w1.weight": "model-00002-of-00006.safetensors",
412
+ "model.layers.9.block_sparse_moe.experts.0.w2.weight": "model-00002-of-00006.safetensors",
413
+ "model.layers.9.block_sparse_moe.experts.0.w3.weight": "model-00002-of-00006.safetensors",
414
+ "model.layers.9.block_sparse_moe.experts.1.w1.weight": "model-00002-of-00006.safetensors",
415
+ "model.layers.9.block_sparse_moe.experts.1.w2.weight": "model-00002-of-00006.safetensors",
416
+ "model.layers.9.block_sparse_moe.experts.1.w3.weight": "model-00002-of-00006.safetensors",
417
+ "model.layers.9.block_sparse_moe.gate.weight": "model-00002-of-00006.safetensors",
418
+ "model.layers.9.input_layernorm.weight": "model-00002-of-00006.safetensors",
419
+ "model.layers.9.post_attention_layernorm.weight": "model-00002-of-00006.safetensors",
420
+ "model.layers.9.self_attn.k_proj.weight": "model-00002-of-00006.safetensors",
421
+ "model.layers.9.self_attn.o_proj.weight": "model-00002-of-00006.safetensors",
422
+ "model.layers.9.self_attn.q_proj.weight": "model-00002-of-00006.safetensors",
423
+ "model.layers.9.self_attn.v_proj.weight": "model-00002-of-00006.safetensors",
424
+ "model.norm.weight": "model-00006-of-00006.safetensors"
425
+ }
426
+ }
special_tokens_map.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<unk>",
4
+ "<s>",
5
+ "</s>"
6
+ ],
7
+ "bos_token": {
8
+ "content": "<s>",
9
+ "lstrip": false,
10
+ "normalized": false,
11
+ "rstrip": false,
12
+ "single_word": false
13
+ },
14
+ "eos_token": {
15
+ "content": "</s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false
20
+ },
21
+ "pad_token": {
22
+ "content": "<s>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false
27
+ },
28
+ "unk_token": {
29
+ "content": "<unk>",
30
+ "lstrip": false,
31
+ "normalized": false,
32
+ "rstrip": false,
33
+ "single_word": false
34
+ }
35
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
3
+ size 493443
tokenizer_config.json ADDED
@@ -0,0 +1,50 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<unk>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<s>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "</s>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ }
29
+ },
30
+ "additional_special_tokens": [
31
+ "<unk>",
32
+ "<s>",
33
+ "</s>"
34
+ ],
35
+ "bos_token": "<s>",
36
+ "clean_up_tokenization_spaces": false,
37
+ "eos_token": "</s>",
38
+ "legacy": true,
39
+ "max_length": null,
40
+ "model_max_length": 255,
41
+ "pad_to_multiple_of": null,
42
+ "pad_token": "<s>",
43
+ "pad_token_type_id": 0,
44
+ "padding_side": "left",
45
+ "sp_model_kwargs": {},
46
+ "spaces_between_special_tokens": false,
47
+ "tokenizer_class": "LlamaTokenizer",
48
+ "unk_token": "<unk>",
49
+ "use_default_system_prompt": true
50
+ }