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#1
by
ben-at-jorah
- opened
- .gitattributes +1 -0
- README.md +43 -0
- config.json +47 -0
- model.safetensors +3 -0
- model.safetensors.index.json +379 -0
- special_tokens_map.json +23 -0
- tokenizer.json +3 -0
- tokenizer_config.json +2063 -0
.gitattributes
CHANGED
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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
ADDED
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@@ -0,0 +1,43 @@
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---
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tags:
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- autotrain
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- text-generation-inference
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- text-generation
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- peft
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- mlx
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library_name: transformers
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base_model: ben-at-jorah/emergency-llama32-1b-finetune-rmsys3
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widget:
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- messages:
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- role: user
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content: What is your favorite condiment?
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license: other
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datasets:
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- ben-at-jorah/emergency-training-data_2024-11-20
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---
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# ben-at-jorah/emergency-llama32-1b-finetune-rmsys3_mlx-8bit
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The Model [ben-at-jorah/emergency-llama32-1b-finetune-rmsys3_mlx-8bit](https://huggingface.co/ben-at-jorah/emergency-llama32-1b-finetune-rmsys3_mlx-8bit) was converted to MLX format from [ben-at-jorah/emergency-llama32-1b-finetune-rmsys3](https://huggingface.co/ben-at-jorah/emergency-llama32-1b-finetune-rmsys3) using mlx-lm version **0.19.2**.
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## Use with mlx
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```bash
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pip install mlx-lm
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```
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```python
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from mlx_lm import load, generate
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model, tokenizer = load("ben-at-jorah/emergency-llama32-1b-finetune-rmsys3_mlx-8bit")
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prompt="hello"
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if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
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messages = [{"role": "user", "content": prompt}]
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prompt = tokenizer.apply_chat_template(
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messages, tokenize=False, add_generation_prompt=True
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)
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response = generate(model, tokenizer, prompt=prompt, verbose=True)
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```
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config.json
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{
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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": [
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128001,
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128008,
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128009
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],
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"head_dim": 64,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 8192,
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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": 16,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"quantization": {
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"group_size": 32,
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"bits": 8
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},
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"quantization_config": {
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"group_size": 32,
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"bits": 8
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},
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 32.0,
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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": true,
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"torch_dtype": "float16",
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"transformers_version": "4.46.2",
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"use_cache": true,
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"vocab_size": 128256
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}
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model.safetensors
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:4548367de5bab7a74ac829b05fc27d46cdda98f04f4af1a3a3a631b2deb0615c
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| 3 |
+
size 1390391768
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model.safetensors.index.json
ADDED
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@@ -0,0 +1,379 @@
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| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 1390350336
|
| 4 |
+
},
|
| 5 |
+
"weight_map": {
|
| 6 |
+
"model.embed_tokens.biases": "model.safetensors",
|
| 7 |
+
"model.embed_tokens.scales": "model.safetensors",
|
| 8 |
+
"model.embed_tokens.weight": "model.safetensors",
|
| 9 |
+
"model.layers.0.input_layernorm.weight": "model.safetensors",
|
| 10 |
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"model.layers.0.mlp.down_proj.biases": "model.safetensors",
|
| 11 |
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"model.layers.0.mlp.down_proj.scales": "model.safetensors",
|
| 12 |
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"model.layers.0.mlp.down_proj.weight": "model.safetensors",
|
| 13 |
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"model.layers.0.mlp.gate_proj.biases": "model.safetensors",
|
| 14 |
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"model.layers.0.mlp.gate_proj.scales": "model.safetensors",
|
| 15 |
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"model.layers.0.mlp.gate_proj.weight": "model.safetensors",
|
| 16 |
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"model.layers.0.mlp.up_proj.biases": "model.safetensors",
|
| 17 |
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"model.layers.0.mlp.up_proj.scales": "model.safetensors",
|
| 18 |
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"model.layers.0.mlp.up_proj.weight": "model.safetensors",
|
| 19 |
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"model.layers.0.post_attention_layernorm.weight": "model.safetensors",
|
| 20 |
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"model.layers.0.self_attn.k_proj.biases": "model.safetensors",
|
| 21 |
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"model.layers.0.self_attn.k_proj.scales": "model.safetensors",
|
| 22 |
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"model.layers.0.self_attn.k_proj.weight": "model.safetensors",
|
| 23 |
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"model.layers.0.self_attn.o_proj.biases": "model.safetensors",
|
| 24 |
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"model.layers.0.self_attn.o_proj.scales": "model.safetensors",
|
| 25 |
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"model.layers.0.self_attn.o_proj.weight": "model.safetensors",
|
| 26 |
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"model.layers.0.self_attn.q_proj.biases": "model.safetensors",
|
| 27 |
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"model.layers.0.self_attn.q_proj.scales": "model.safetensors",
|
| 28 |
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"model.layers.0.self_attn.q_proj.weight": "model.safetensors",
|
| 29 |
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"model.layers.0.self_attn.v_proj.biases": "model.safetensors",
|
| 30 |
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"model.layers.0.self_attn.v_proj.scales": "model.safetensors",
|
| 31 |
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"model.layers.0.self_attn.v_proj.weight": "model.safetensors",
|
| 32 |
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"model.layers.1.input_layernorm.weight": "model.safetensors",
|
| 33 |
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"model.layers.1.mlp.down_proj.biases": "model.safetensors",
|
| 34 |
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"model.layers.1.mlp.down_proj.scales": "model.safetensors",
|
| 35 |
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"model.layers.1.mlp.down_proj.weight": "model.safetensors",
|
| 36 |
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"model.layers.1.mlp.gate_proj.biases": "model.safetensors",
|
| 37 |
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"model.layers.1.mlp.gate_proj.scales": "model.safetensors",
|
| 38 |
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"model.layers.1.mlp.gate_proj.weight": "model.safetensors",
|
| 39 |
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special_tokens_map.json
ADDED
|
@@ -0,0 +1,23 @@
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|
| 1 |
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{
|
| 2 |
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"bos_token": {
|
| 3 |
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"content": "<|begin_of_text|>",
|
| 4 |
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"lstrip": false,
|
| 5 |
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"normalized": false,
|
| 6 |
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|
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| 8 |
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"eos_token": {
|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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|
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|
| 20 |
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|
| 21 |
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"single_word": false
|
| 22 |
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|
| 23 |
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|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
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size 17209920
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tokenizer_config.json
ADDED
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@@ -0,0 +1,2063 @@
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|
| 1 |
+
{
|
| 2 |
+
"added_tokens_decoder": {
|
| 3 |
+
"128000": {
|
| 4 |
+
"content": "<|begin_of_text|>",
|
| 5 |
+
"lstrip": false,
|
| 6 |
+
"normalized": false,
|
| 7 |
+
"rstrip": false,
|
| 8 |
+
"single_word": false,
|
| 9 |
+
"special": true
|
| 10 |
+
},
|
| 11 |
+
"128001": {
|
| 12 |
+
"content": "<|end_of_text|>",
|
| 13 |
+
"lstrip": false,
|
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| 1849 |
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| 1850 |
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| 1851 |
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|
| 1858 |
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|
| 1859 |
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|
| 1860 |
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| 1861 |
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| 1865 |
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|
| 1866 |
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| 1867 |
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|
| 1868 |
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|
| 1869 |
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| 1870 |
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|
| 1876 |
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| 1877 |
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|
| 1882 |
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|
| 1883 |
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|
| 1884 |
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|
| 1885 |
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|
| 1886 |
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|
| 1887 |
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| 1888 |
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|
| 1889 |
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|
| 1890 |
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|
| 1891 |
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|
| 1892 |
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|
| 1893 |
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|
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|
| 1895 |
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| 1896 |
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|
| 1897 |
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|
| 1898 |
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|
| 1899 |
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|
| 1900 |
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|
| 1901 |
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| 1902 |
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| 1904 |
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| 1905 |
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|
| 1906 |
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| 1907 |
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|
| 1908 |
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|
| 1909 |
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|
| 1910 |
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| 1911 |
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| 1913 |
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|
| 1914 |
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| 1915 |
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|
| 1916 |
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|
| 1917 |
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| 1918 |
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| 1919 |
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| 1920 |
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| 1921 |
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|
| 1922 |
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|
| 1923 |
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|
| 1924 |
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|
| 1925 |
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| 1926 |
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|
| 1927 |
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| 1928 |
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| 1929 |
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|
| 1930 |
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| 1931 |
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|
| 1932 |
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|
| 1933 |
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| 1934 |
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|
| 1935 |
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| 1936 |
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| 1937 |
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|
| 1938 |
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| 1939 |
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|
| 1940 |
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|
| 1941 |
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| 1942 |
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| 1943 |
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| 1944 |
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| 1945 |
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|
| 1946 |
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| 1947 |
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|
| 1948 |
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|
| 1949 |
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| 1950 |
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|
| 1951 |
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| 1952 |
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| 1953 |
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|
| 1954 |
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|
| 1955 |
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|
| 1956 |
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|
| 1957 |
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| 1958 |
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| 1959 |
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| 1960 |
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| 1961 |
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|
| 1962 |
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|
| 1963 |
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|
| 1964 |
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|
| 1965 |
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| 1966 |
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|
| 1967 |
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| 1968 |
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| 1969 |
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|
| 1970 |
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|
| 1971 |
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|
| 1972 |
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|
| 1973 |
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|
| 1974 |
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| 1975 |
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| 1976 |
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|
| 1977 |
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|
| 1978 |
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|
| 1979 |
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|
| 1980 |
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|
| 1981 |
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|
| 1982 |
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|
| 1983 |
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| 1984 |
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| 1985 |
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|
| 1986 |
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|
| 1987 |
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|
| 1988 |
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|
| 1989 |
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|
| 1990 |
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|
| 1991 |
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| 1992 |
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|
| 1993 |
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|
| 1994 |
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|
| 1995 |
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|
| 1996 |
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|
| 1997 |
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| 1998 |
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| 1999 |
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| 2000 |
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| 2001 |
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|
| 2002 |
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|
| 2003 |
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|
| 2004 |
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|
| 2005 |
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| 2006 |
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| 2007 |
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| 2008 |
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|
| 2009 |
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|
| 2010 |
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|
| 2011 |
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|
| 2012 |
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|
| 2013 |
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| 2014 |
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| 2015 |
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| 2016 |
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| 2017 |
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|
| 2018 |
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|
| 2019 |
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|
| 2020 |
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"content": "<|reserved_special_token_244|>",
|
| 2021 |
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| 2022 |
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| 2023 |
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| 2024 |
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| 2025 |
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| 2026 |
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| 2027 |
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|
| 2028 |
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|
| 2029 |
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|
| 2030 |
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| 2031 |
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| 2032 |
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| 2033 |
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| 2034 |
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| 2035 |
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| 2036 |
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| 2037 |
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| 2038 |
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| 2040 |
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| 2041 |
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| 2042 |
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| 2044 |
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| 2045 |
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| 2048 |
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| 2049 |
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| 2050 |
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| 2051 |
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| 2052 |
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|
| 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 {%- if strftime_now is defined %}\n {%- set date_string = strftime_now(\"%d %b %Y\") %}\n {%- else %}\n {%- set date_string = \"26 Jul 2024\" %}\n {%- endif %}\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 #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if tools is not none %}\n {{- \"Environment: ipython\\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 {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {{- \"<|eot_id|>\" }}\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": 2048,
|
| 2061 |
+
"pad_token": "<|eot_id|>",
|
| 2062 |
+
"tokenizer_class": "PreTrainedTokenizerFast"
|
| 2063 |
+
}
|