End of training
Browse files- README.md +61 -0
- config.json +35 -0
- generation_config.json +9 -0
- model-00001-of-00006.safetensors +3 -0
- model-00002-of-00006.safetensors +3 -0
- model-00003-of-00006.safetensors +3 -0
- model-00004-of-00006.safetensors +3 -0
- model-00005-of-00006.safetensors +3 -0
- model-00006-of-00006.safetensors +3 -0
- model.safetensors.index.json +298 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer_config.json +2082 -0
- trainer_state.json +3129 -0
- training_args.bin +3 -0
README.md
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---
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library_name: transformers
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license: llama3
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base_model: NousResearch/Hermes-3-Llama-3.1-8B
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tags:
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- trl
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- sft
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- generated_from_trainer
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model-index:
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- name: full
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# full
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This model is a fine-tuned version of [NousResearch/Hermes-3-Llama-3.1-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B) on the None dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 2
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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- total_eval_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.03
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- num_epochs: 3
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### Training results
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.2.0
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- Datasets 3.0.0
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "NousResearch/Hermes-3-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": 128040,
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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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"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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"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": "float32",
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"transformers_version": "4.44.2",
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"use_cache": false,
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"vocab_size": 128257
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}
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generation_config.json
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"eos_token_id": 128040,
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.44.2"
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}
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model-00001-of-00006.safetensors
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special_tokens_map.json
ADDED
@@ -0,0 +1,30 @@
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|
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|
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|
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|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
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tokenizer_config.json
ADDED
@@ -0,0 +1,2082 @@
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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,
|
14 |
+
"normalized": false,
|
15 |
+
"rstrip": false,
|
16 |
+
"single_word": false,
|
17 |
+
"special": true
|
18 |
+
},
|
19 |
+
"128002": {
|
20 |
+
"content": "<tool_call>",
|
21 |
+
"lstrip": false,
|
22 |
+
"normalized": false,
|
23 |
+
"rstrip": false,
|
24 |
+
"single_word": false,
|
25 |
+
"special": false
|
26 |
+
},
|
27 |
+
"128003": {
|
28 |
+
"content": "<tool_response>",
|
29 |
+
"lstrip": false,
|
30 |
+
"normalized": false,
|
31 |
+
"rstrip": false,
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1793 |
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|
1794 |
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|
1795 |
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|
1796 |
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|
1797 |
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|
1798 |
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|
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|
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|
1801 |
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|
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|
1803 |
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|
1804 |
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|
1805 |
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|
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|
1807 |
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|
1808 |
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|
1809 |
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|
1810 |
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|
1811 |
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|
1812 |
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|
1813 |
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|
1814 |
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|
1815 |
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|
1816 |
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|
1817 |
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|
1818 |
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|
1819 |
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|
1820 |
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|
1821 |
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|
1822 |
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|
1823 |
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|
1824 |
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"single_word": false,
|
1825 |
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"special": true
|
1826 |
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|
1827 |
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"128228": {
|
1828 |
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"content": "<|reserved_special_token_220|>",
|
1829 |
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|
1830 |
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|
1831 |
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|
1832 |
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"single_word": false,
|
1833 |
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"special": true
|
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|
1835 |
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|
1836 |
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|
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|
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|
1839 |
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|
1840 |
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"single_word": false,
|
1841 |
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"special": true
|
1842 |
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|
1843 |
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"128230": {
|
1844 |
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|
1845 |
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|
1846 |
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|
1847 |
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|
1848 |
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|
1849 |
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|
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|
1851 |
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|
1852 |
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|
1853 |
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|
1854 |
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|
1855 |
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|
1856 |
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|
1857 |
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"special": true
|
1858 |
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|
1859 |
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|
1860 |
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|
1861 |
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|
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|
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|
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|
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|
1867 |
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|
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|
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|
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|
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|
1875 |
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|
1876 |
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|
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|
1880 |
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|
1881 |
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"special": true
|
1882 |
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|
1883 |
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|
1884 |
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1885 |
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|
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|
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|
1888 |
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|
1889 |
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"special": true
|
1890 |
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1891 |
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|
1892 |
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|
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|
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|
1900 |
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|
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|
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|
1908 |
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1910 |
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|
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|
1912 |
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|
1913 |
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|
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1915 |
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|
1916 |
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|
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|
1920 |
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|
1921 |
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|
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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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"content": "<|reserved_special_token_233|>",
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1933 |
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|
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|
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|
1936 |
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|
1937 |
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|
1938 |
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},
|
1939 |
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"128242": {
|
1940 |
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"content": "<|reserved_special_token_234|>",
|
1941 |
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|
1942 |
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|
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|
1944 |
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"single_word": false,
|
1945 |
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|
1946 |
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},
|
1947 |
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"128243": {
|
1948 |
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"content": "<|reserved_special_token_235|>",
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1949 |
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|
1950 |
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|
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|
1952 |
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|
1953 |
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|
1954 |
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},
|
1955 |
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"128244": {
|
1956 |
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"content": "<|reserved_special_token_236|>",
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1957 |
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|
1958 |
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|
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|
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|
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|
1962 |
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|
1963 |
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|
1964 |
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"content": "<|reserved_special_token_237|>",
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1965 |
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|
1966 |
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|
1967 |
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"rstrip": false,
|
1968 |
+
"single_word": false,
|
1969 |
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"special": true
|
1970 |
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},
|
1971 |
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"128246": {
|
1972 |
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"content": "<|reserved_special_token_238|>",
|
1973 |
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|
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|
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|
1976 |
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"single_word": false,
|
1977 |
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"special": true
|
1978 |
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},
|
1979 |
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"128247": {
|
1980 |
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"content": "<|reserved_special_token_239|>",
|
1981 |
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|
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|
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|
1984 |
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"single_word": false,
|
1985 |
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"special": true
|
1986 |
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},
|
1987 |
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"128248": {
|
1988 |
+
"content": "<|reserved_special_token_240|>",
|
1989 |
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|
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|
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|
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|
1993 |
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"special": true
|
1994 |
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},
|
1995 |
+
"128249": {
|
1996 |
+
"content": "<|reserved_special_token_241|>",
|
1997 |
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|
1998 |
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|
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|
2000 |
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"single_word": false,
|
2001 |
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"special": true
|
2002 |
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},
|
2003 |
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"128250": {
|
2004 |
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"content": "<|reserved_special_token_242|>",
|
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|
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|
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|
2008 |
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"single_word": false,
|
2009 |
+
"special": true
|
2010 |
+
},
|
2011 |
+
"128251": {
|
2012 |
+
"content": "<|reserved_special_token_243|>",
|
2013 |
+
"lstrip": false,
|
2014 |
+
"normalized": false,
|
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+
"rstrip": false,
|
2016 |
+
"single_word": false,
|
2017 |
+
"special": true
|
2018 |
+
},
|
2019 |
+
"128252": {
|
2020 |
+
"content": "<|reserved_special_token_244|>",
|
2021 |
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|
2022 |
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|
2023 |
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"rstrip": false,
|
2024 |
+
"single_word": false,
|
2025 |
+
"special": true
|
2026 |
+
},
|
2027 |
+
"128253": {
|
2028 |
+
"content": "<|reserved_special_token_245|>",
|
2029 |
+
"lstrip": false,
|
2030 |
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"normalized": false,
|
2031 |
+
"rstrip": false,
|
2032 |
+
"single_word": false,
|
2033 |
+
"special": true
|
2034 |
+
},
|
2035 |
+
"128254": {
|
2036 |
+
"content": "<|reserved_special_token_246|>",
|
2037 |
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"lstrip": false,
|
2038 |
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"normalized": false,
|
2039 |
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"rstrip": false,
|
2040 |
+
"single_word": false,
|
2041 |
+
"special": true
|
2042 |
+
},
|
2043 |
+
"128255": {
|
2044 |
+
"content": "<|reserved_special_token_247|>",
|
2045 |
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"lstrip": false,
|
2046 |
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"normalized": false,
|
2047 |
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"rstrip": false,
|
2048 |
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"single_word": false,
|
2049 |
+
"special": true
|
2050 |
+
},
|
2051 |
+
"128256": {
|
2052 |
+
"content": "<unk>",
|
2053 |
+
"lstrip": false,
|
2054 |
+
"normalized": false,
|
2055 |
+
"rstrip": false,
|
2056 |
+
"single_word": false,
|
2057 |
+
"special": true
|
2058 |
+
}
|
2059 |
+
},
|
2060 |
+
"bos_token": "<|begin_of_text|>",
|
2061 |
+
"chat_template": [
|
2062 |
+
{
|
2063 |
+
"name": "default",
|
2064 |
+
"template": "{{bos_token}}{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}"
|
2065 |
+
},
|
2066 |
+
{
|
2067 |
+
"name": "tool_use",
|
2068 |
+
"template": "{%- macro json_to_python_type(json_spec) %}\n{%- set basic_type_map = {\n \"string\": \"str\",\n \"number\": \"float\",\n \"integer\": \"int\",\n \"boolean\": \"bool\"\n} %}\n\n{%- if basic_type_map[json_spec.type] is defined %}\n {{- basic_type_map[json_spec.type] }}\n{%- elif json_spec.type == \"array\" %}\n {{- \"list[\" + json_to_python_type(json_spec|items) + \"]\"}}\n{%- elif json_spec.type == \"object\" %}\n {%- if json_spec.additionalProperties is defined %}\n {{- \"dict[str, \" + json_to_python_type(json_spec.additionalProperties) + ']'}}\n {%- else %}\n {{- \"dict\" }}\n {%- endif %}\n{%- elif json_spec.type is iterable %}\n {{- \"Union[\" }}\n {%- for t in json_spec.type %}\n {{- json_to_python_type({\"type\": t}) }}\n {%- if not loop.last %}\n {{- \",\" }} \n {%- endif %}\n {%- endfor %}\n {{- \"]\" }}\n{%- else %}\n {{- \"Any\" }}\n{%- endif %}\n{%- endmacro %}\n\n\n{{- bos_token }}\n{{- '<|im_start|>system\n' }}\n{{- \"You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools: <tools> \" }}\n{%- for tool in tools %}\n {%- if tool.function is defined %}\n {%- set tool = tool.function %}\n {%- endif %}\n {{- '{\"type\": \"function\", \"function\": ' }}\n {{- '{\"name\": \"' + tool.name + '\", ' }}\n {{- '\"description\": \"' + tool.name + '(' }}\n {%- for param_name, param_fields in tool.parameters.properties|items %}\n {{- param_name + \": \" + json_to_python_type(param_fields) }}\n {%- if not loop.last %}\n {{- \", \" }}\n {%- endif %}\n {%- endfor %}\n {{- \")\" }}\n {%- if tool.return is defined %}\n {{- \" -> \" + json_to_python_type(tool.return) }}\n {%- endif %}\n {{- \" - \" + tool.description + \"\n\n\" }}\n {%- for param_name, param_fields in tool.parameters.properties|items %}\n {%- if loop.first %}\n {{- \" Args:\n\" }}\n {%- endif %}\n {{- \" \" + param_name + \"(\" + json_to_python_type(param_fields) + \"): \" + param_fields.description|trim }}\n {%- endfor %}\n {%- if tool.return is defined and tool.return.description is defined %}\n {{- \"\n Returns:\n \" + tool.return.description }}\n {%- endif %}\n {{- '\"' }}\n {{- ', \"parameters\": ' }}\n {%- if tool.parameters.properties | length == 0 %}\n {{- \"{}\" }}\n {%- else %}\n {{- tool.parameters|tojson }}\n {%- endif %}\n {{- \"}\" }}\n {%- if not loop.last %}\n {{- \"\n\" }}\n {%- endif %}\n{%- endfor %}\n{{- \" </tools>\" }}\n{{- 'Use the following pydantic model json schema for each tool call you will make: {\"properties\": {\"name\": {\"title\": \"Name\", \"type\": \"string\"}, \"arguments\": {\"title\": \"Arguments\", \"type\": \"object\"}}, \"required\": [\"name\", \"arguments\"], \"title\": \"FunctionCall\", \"type\": \"object\"}}\n' }}\n{{- \"For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:\n\" }}\n{{- \"<tool_call>\n\" }}\n{{- '{\"name\": <function-name>, \"arguments\": <args-dict>}\n' }}\n{{- '</tool_call><|im_end|>\n' }}\n{%- for message in messages %}\n {%- if message.role == \"user\" or message.role == \"system\" or (message.role == \"assistant\" and message.tool_calls is not defined) %}\n {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- for tool_call in message.tool_calls %}\n {{- '\n<tool_call>\n' }} {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '{' }}\n {{- '\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\"' }}\n {{- ', '}}\n {%- if tool_call.arguments is defined %}\n {{- '\"arguments\": ' }}\n {%- if tool_call.arguments is string %}\n {{- tool_call.arguments }}\n {%- else %}\n {{- tool_call.arguments|tojson }}\n {%- endif %}\n {%- endif %}\n {{- '}' }}\n {{- '\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n {{- '<|im_start|>tool\n' }}\n {%- endif %}\n {{- '<tool_response>\n' }}\n {{- message.content }}\n {%- if not loop.last %}\n {{- '\n</tool_response>\n' }}\n {%- else %}\n {{- '\n</tool_response>' }}\n {%- endif %}\n {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n {{- '<|im_end|>' }}\n {%- elif loop.last %}\n {{- '<|im_end|>' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\n' }}\n{%- endif %}\n"
|
2069 |
+
}
|
2070 |
+
],
|
2071 |
+
"clean_up_tokenization_spaces": true,
|
2072 |
+
"eos_token": "<|im_end|>",
|
2073 |
+
"model_input_names": [
|
2074 |
+
"input_ids",
|
2075 |
+
"attention_mask"
|
2076 |
+
],
|
2077 |
+
"model_max_length": 1024,
|
2078 |
+
"pad_token": "<|im_end|>",
|
2079 |
+
"padding_side": "right",
|
2080 |
+
"tokenizer_class": "PreTrainedTokenizerFast",
|
2081 |
+
"unk_token": "<unk>"
|
2082 |
+
}
|
trainer_state.json
ADDED
@@ -0,0 +1,3129 @@
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