Model save
Browse files- README.md +58 -0
- all_results.json +8 -0
- generation_config.json +9 -0
- model-00001-of-00007.safetensors +1 -1
- model-00002-of-00007.safetensors +1 -1
- model-00003-of-00007.safetensors +1 -1
- model-00004-of-00007.safetensors +1 -1
- model-00005-of-00007.safetensors +1 -1
- model-00006-of-00007.safetensors +1 -1
- model-00007-of-00007.safetensors +1 -1
- train_results.json +8 -0
- trainer_state.json +0 -0
- training.log +1 -0
README.md
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---
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base_model: deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct
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library_name: transformers
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model_name: Deepseek-Coder-V2-Lite-13B-Instruct-sft-s1K
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tags:
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- generated_from_trainer
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- trl
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- sft
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licence: license
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---
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# Model Card for Deepseek-Coder-V2-Lite-13B-Instruct-sft-s1K
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This model is a fine-tuned version of [deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct](https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct).
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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="HectorHe/Deepseek-Coder-V2-Lite-13B-Instruct-sft-s1K", 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/hector_-carnegie-mellon-university/huggingface/runs/nkgydwm9)
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This model was trained with SFT.
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### Framework versions
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- TRL: 0.18.0.dev0
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- Transformers: 4.52.0.dev0
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- Pytorch: 2.6.0
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- Datasets: 4.0.0
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- Tokenizers: 0.21.4
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## Citations
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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 Gallou{\'e}dec},
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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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all_results.json
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{
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"total_flos": 40609159823360.0,
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"train_loss": 0.6996430353867099,
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"train_runtime": 32431.1921,
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"train_samples": 1000,
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"train_samples_per_second": 0.274,
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"train_steps_per_second": 0.034
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 100000,
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"do_sample": true,
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"eos_token_id": 100001,
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"temperature": 0.3,
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"top_p": 0.95,
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"transformers_version": "4.52.0.dev0"
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}
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model-00001-of-00007.safetensors
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model-00002-of-00007.safetensors
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train_results.json
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{
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"total_flos": 40609159823360.0,
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"train_loss": 0.6996430353867099,
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"train_runtime": 32431.1921,
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"train_samples": 1000,
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"train_samples_per_second": 0.274,
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"train_steps_per_second": 0.034
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}
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trainer_state.json
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training.log
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(lm_head): Linear(in_features=2048, out_features=102400, bias=False)
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)
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(lm_head): Linear(in_features=2048, out_features=102400, bias=False)
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)
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2025-08-14 03:40:52 - INFO - __main__ - *** Save model ***
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