Model save
Browse files- .gitattributes +1 -0
- README.md +68 -0
- added_tokens.json +24 -0
- all_results.json +8 -0
- config.json +30 -0
- generation_config.json +6 -0
- merges.txt +0 -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 +346 -0
- special_tokens_map.json +31 -0
- tokenizer.json +3 -0
- tokenizer_config.json +209 -0
- train_results.json +8 -0
- trainer_state.json +126 -0
- training_args.bin +3 -0
- vocab.json +0 -0
.gitattributes
CHANGED
@@ -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: Qwen/Qwen2.5-7B
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library_name: transformers
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model_name: Qwen-2.5-7B
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tags:
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- generated_from_trainer
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- trl
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- grpo
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licence: license
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---
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# Model Card for Qwen-2.5-7B
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This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="Dongwei/Qwen-2.5-7B", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/dongwei_jiang/huggingface/runs/ya0i8esg)
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This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
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### Framework versions
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- TRL: 0.15.0.dev0
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- Transformers: 4.49.0.dev0
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- Pytorch: 2.5.1+cu121
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- Datasets: 3.2.0
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- Tokenizers: 0.21.0
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## Citations
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Cite GRPO as:
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```bibtex
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@article{zhihong2024deepseekmath,
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title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
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author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
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year = 2024,
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eprint = {arXiv:2402.03300},
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}
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```
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Cite TRL as:
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```bibtex
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@misc{vonwerra2022trl,
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title = {{TRL: Transformer Reinforcement Learning}},
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author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
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year = 2020,
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journal = {GitHub repository},
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publisher = {GitHub},
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howpublished = {\url{https://github.com/huggingface/trl}}
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}
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```
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added_tokens.json
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}
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all_results.json
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{
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"total_flos": 0.0,
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"train_loss": 0.018138731037502857,
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}
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config.json
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{
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"_name_or_path": "Qwen/Qwen2.5-7B",
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"max_position_embeddings": 131072,
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"max_window_layers": 28,
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"model_type": "qwen2",
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"num_attention_heads": 28,
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"num_hidden_layers": 28,
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"num_key_value_heads": 4,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.49.0.dev0",
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"use_cache": false,
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"use_mrope": false,
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"use_sliding_window": false,
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"vocab_size": 152064
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}
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generation_config.json
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merges.txt
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The diff for this file is too large to render.
See raw diff
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model-00001-of-00004.safetensors
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|
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|
111 |
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|
112 |
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training_args.bin
ADDED
@@ -0,0 +1,3 @@
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|
1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:61b1f73f5bd8ce79b567265f023e15199a462b840dfa220650df8e9987058579
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size 6968
|
vocab.json
ADDED
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|
|