82 lines
2.6 KiB
Markdown
82 lines
2.6 KiB
Markdown
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---
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base_model: Qwen/Qwen2.5-7B-Instruct
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library_name: transformers
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model_name: qwen2.5-7b-hpm-socsci210
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tags:
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- generated_from_trainer
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- trackio:https://AstralFellows-ml-intern-hpm00001.hf.space?project=human-process-model&runs=qwen2.5-7b-socsci210-sft-v1&sidebar=collapsed
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- sft
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- trl
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- hf_jobs
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- ml-intern
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licence: license
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---
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# Model Card for qwen2.5-7b-hpm-socsci210
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This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-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="AstralFellows/qwen2.5-7b-hpm-socsci210", 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/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" width="150" height="24"/>](https://AstralFellows-ml-intern-hpm00001.hf.space?project=human-process-model&runs=qwen2.5-7b-socsci210-sft-v1&sidebar=collapsed)
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This model was trained with SFT.
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### Framework versions
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- TRL: 1.6.0
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- Transformers: 5.12.1
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- Pytorch: 2.7.1
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- Datasets: 5.0.0
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- Tokenizers: 0.22.2
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## Citations
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Cite TRL as:
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```bibtex
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@software{vonwerra2020trl,
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title = {{TRL: Transformers Reinforcement Learning}},
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author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
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license = {Apache-2.0},
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url = {https://github.com/huggingface/trl},
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year = {2020}
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}
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```
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<!-- ml-intern-provenance -->
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## Generated by ML Intern
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This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub.
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- Try ML Intern: https://smolagents-ml-intern.hf.space
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- Source code: https://github.com/huggingface/ml-intern
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = 'AstralFellows/qwen2.5-7b-hpm-socsci210'
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id)
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```
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For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class.
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