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Browse files- .gitattributes +1 -0
- README.md +51 -0
- config.json +38 -0
- mergekit_config.yml +18 -0
- model-00001-of-00004.safetensors +3 -0
- model-00002-of-00004.safetensors +3 -0
- model-00003-of-00004.safetensors +3 -0
- model-00004-of-00004.safetensors +3 -0
- model.safetensors.index.json +1 -0
- special_tokens_map.json +23 -0
- tokenizer.json +3 -0
- tokenizer_config.json +2064 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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base_model:
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- unsloth/Meta-Llama-3.1-8B
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- qingy2024/NaturalLM3-8B-Instruct-v0.1
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- NousResearch/Hermes-3-Llama-3.1-8B
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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# merge
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [unsloth/Meta-Llama-3.1-8B](https://huggingface.co/unsloth/Meta-Llama-3.1-8B) as a base.
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### Models Merged
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The following models were included in the merge:
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* [qingy2024/NaturalLM3-8B-Instruct-v0.1](https://huggingface.co/qingy2024/NaturalLM3-8B-Instruct-v0.1)
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* [NousResearch/Hermes-3-Llama-3.1-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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models:
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- model: qingy2024/NaturalLM3-8B-Instruct-v0.1
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parameters:
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weight: 1
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density: 1
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- model: NousResearch/Hermes-3-Llama-3.1-8B
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parameters:
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weight: 1
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density: 1
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merge_method: ties
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base_model: unsloth/Meta-Llama-3.1-8B
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parameters:
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weight: 1
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density: 1
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normalize: true
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int8_mask: true
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tokenizer_source: qingy2024/NaturalLM3-8B-Instruct-v0.1
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dtype: bfloat16
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```
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config.json
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{
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"_name_or_path": "unsloth/Meta-Llama-3.1-8B",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": 128001,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pad_token_id": 128004,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 8.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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},
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.46.2",
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"unsloth_version": "2024.9",
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"use_cache": true,
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"vocab_size": 128256
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}
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mergekit_config.yml
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models:
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- model: qingy2024/NaturalLM3-8B-Instruct-v0.1
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parameters:
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weight: 1
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density: 1
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- model: NousResearch/Hermes-3-Llama-3.1-8B
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parameters:
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weight: 1
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density: 1
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merge_method: ties
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base_model: unsloth/Meta-Llama-3.1-8B
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parameters:
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weight: 1
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density: 1
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normalize: true
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int8_mask: true
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tokenizer_source: qingy2024/NaturalLM3-8B-Instruct-v0.1
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dtype: bfloat16
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1 |
+
{
|
2 |
+
"added_tokens_decoder": {
|
3 |
+
"128000": {
|
4 |
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"content": "<|begin_of_text|>",
|
5 |
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|
6 |
+
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|
7 |
+
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|
8 |
+
"single_word": false,
|
9 |
+
"special": true
|
10 |
+
},
|
11 |
+
"128001": {
|
12 |
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"content": "<|end_of_text|>",
|
13 |
+
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|
14 |
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|
15 |
+
"rstrip": false,
|
16 |
+
"single_word": false,
|
17 |
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"special": true
|
18 |
+
},
|
19 |
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"128002": {
|
20 |
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"content": "<|reserved_special_token_0|>",
|
21 |
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|
22 |
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|
23 |
+
"rstrip": false,
|
24 |
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|
25 |
+
"special": true
|
26 |
+
},
|
27 |
+
"128003": {
|
28 |
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"content": "<|reserved_special_token_1|>",
|
29 |
+
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|
30 |
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|
31 |
+
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|
32 |
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|
33 |
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|
34 |
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},
|
35 |
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"128004": {
|
36 |
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"content": "<|finetune_right_pad_id|>",
|
37 |
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"lstrip": false,
|
38 |
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"normalized": false,
|
39 |
+
"rstrip": false,
|
40 |
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|
41 |
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|
42 |
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},
|
43 |
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|
44 |
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"content": "<|reserved_special_token_2|>",
|
45 |
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|
46 |
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|
47 |
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|
48 |
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|
49 |
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|
50 |
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|
51 |
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|
52 |
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"content": "<|start_header_id|>",
|
53 |
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|
54 |
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|
55 |
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|
56 |
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|
57 |
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|
58 |
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|
59 |
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|
60 |
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"content": "<|end_header_id|>",
|
61 |
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|
62 |
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|
63 |
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|
64 |
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|
65 |
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|
66 |
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|
67 |
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|
68 |
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|
69 |
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|
70 |
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|
71 |
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|
72 |
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73 |
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|
74 |
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|
75 |
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|
76 |
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|
77 |
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|
78 |
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|
79 |
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|
80 |
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|
81 |
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|
82 |
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|
83 |
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|
84 |
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|
85 |
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|
86 |
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|
87 |
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|
88 |
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|
89 |
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|
90 |
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|
91 |
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|
92 |
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|
93 |
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94 |
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95 |
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96 |
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|
97 |
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|
98 |
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|
99 |
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|
100 |
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"content": "<|reserved_special_token_4|>",
|
101 |
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|
102 |
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|
103 |
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|
104 |
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|
105 |
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|
106 |
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},
|
107 |
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|
108 |
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|
109 |
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|
110 |
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|
111 |
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|
112 |
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|
113 |
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|
114 |
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},
|
115 |
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|
116 |
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|
117 |
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118 |
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|
119 |
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|
120 |
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|
121 |
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|
122 |
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|
123 |
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|
124 |
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|
125 |
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|
126 |
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|
127 |
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|
128 |
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|
129 |
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|
130 |
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|
131 |
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|
132 |
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|
133 |
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134 |
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135 |
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136 |
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|
137 |
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|
138 |
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|
139 |
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|
140 |
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|
141 |
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|
142 |
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|
143 |
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|
144 |
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|
145 |
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|
146 |
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},
|
147 |
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|
148 |
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"content": "<|reserved_special_token_10|>",
|
149 |
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|
150 |
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|
151 |
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|
152 |
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|
153 |
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|
154 |
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|
155 |
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|
156 |
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|
157 |
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|
158 |
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|
159 |
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|
160 |
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|
161 |
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|
162 |
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|
163 |
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|
164 |
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|
165 |
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|
166 |
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|
167 |
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|
168 |
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|
169 |
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|
170 |
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|
171 |
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|
172 |
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"content": "<|reserved_special_token_13|>",
|
173 |
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|
174 |
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|
175 |
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|
176 |
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|
177 |
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|
178 |
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|
179 |
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|
180 |
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|
181 |
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|
182 |
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|
183 |
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|
184 |
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|
185 |
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|
186 |
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},
|
187 |
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|
188 |
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"content": "<|reserved_special_token_15|>",
|
189 |
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|
190 |
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|
191 |
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|
192 |
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|
193 |
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|
194 |
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|
195 |
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|
196 |
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"content": "<|reserved_special_token_16|>",
|
197 |
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|
198 |
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|
199 |
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|
200 |
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|
201 |
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|
202 |
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},
|
203 |
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|
204 |
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"content": "<|reserved_special_token_17|>",
|
205 |
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|
206 |
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|
207 |
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|
208 |
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|
209 |
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|
210 |
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},
|
211 |
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|
212 |
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"content": "<|reserved_special_token_18|>",
|
213 |
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|
214 |
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|
215 |
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|
216 |
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|
217 |
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|
218 |
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|
219 |
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|
220 |
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|
221 |
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|
222 |
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|
223 |
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|
224 |
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|
225 |
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|
226 |
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|
227 |
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|
228 |
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"content": "<|reserved_special_token_20|>",
|
229 |
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|
230 |
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|
231 |
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|
232 |
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|
233 |
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|
234 |
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|
235 |
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|
236 |
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|
237 |
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|
238 |
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|
239 |
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|
240 |
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|
241 |
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|
242 |
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|
243 |
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|
244 |
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|
245 |
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246 |
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247 |
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248 |
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249 |
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|
250 |
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|
251 |
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|
252 |
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|
253 |
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254 |
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255 |
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256 |
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257 |
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258 |
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259 |
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|
260 |
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|
261 |
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262 |
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263 |
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264 |
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265 |
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266 |
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267 |
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|
268 |
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|
269 |
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|
270 |
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271 |
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272 |
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273 |
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274 |
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275 |
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|
276 |
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|
277 |
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278 |
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279 |
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280 |
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2025 |
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"special": true
|
2026 |
+
},
|
2027 |
+
"128253": {
|
2028 |
+
"content": "<|reserved_special_token_245|>",
|
2029 |
+
"lstrip": false,
|
2030 |
+
"normalized": false,
|
2031 |
+
"rstrip": false,
|
2032 |
+
"single_word": false,
|
2033 |
+
"special": true
|
2034 |
+
},
|
2035 |
+
"128254": {
|
2036 |
+
"content": "<|reserved_special_token_246|>",
|
2037 |
+
"lstrip": false,
|
2038 |
+
"normalized": false,
|
2039 |
+
"rstrip": false,
|
2040 |
+
"single_word": false,
|
2041 |
+
"special": true
|
2042 |
+
},
|
2043 |
+
"128255": {
|
2044 |
+
"content": "<|reserved_special_token_247|>",
|
2045 |
+
"lstrip": false,
|
2046 |
+
"normalized": false,
|
2047 |
+
"rstrip": false,
|
2048 |
+
"single_word": false,
|
2049 |
+
"special": true
|
2050 |
+
}
|
2051 |
+
},
|
2052 |
+
"bos_token": "<|begin_of_text|>",
|
2053 |
+
"chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n {%- for arg_name, arg_val in tool_call.arguments | items %}\n {{- arg_name + '=\"' + arg_val + '\"' }}\n {%- if not loop.last %}\n {{- \", \" }}\n {%- endif %}\n {%- endfor %}\n {{- \")\" }}\n {%- else %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {%- endif %}\n {%- if builtin_tools is defined %}\n {#- This means we're in ipython mode #}\n {{- \"<|eom_id|>\" }}\n {%- else %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
|
2054 |
+
"clean_up_tokenization_spaces": true,
|
2055 |
+
"eos_token": "<|eot_id|>",
|
2056 |
+
"model_input_names": [
|
2057 |
+
"input_ids",
|
2058 |
+
"attention_mask"
|
2059 |
+
],
|
2060 |
+
"model_max_length": 131072,
|
2061 |
+
"pad_token": "<|finetune_right_pad_id|>",
|
2062 |
+
"padding_side": "left",
|
2063 |
+
"tokenizer_class": "PreTrainedTokenizerFast"
|
2064 |
+
}
|