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Model: lewtun/SmolLM2-360M-SFT-everyday-conversations Source: Original Platform
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README.md
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base_model: HuggingFaceTB/SmolLM2-360M
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library_name: transformers
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model_name: SmolLM2-360M-SFT-everyday-conversations
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tags:
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- generated_from_trainer
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- trackio:https://lewtun-mlintern-smolsft1.hf.space?project=huggingface&runs=sft-smollm2-360m-everyday-conversations&sidebar=collapsed
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- hf_jobs
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- sft
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- trl
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licence: license
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---
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# Model Card for SmolLM2-360M-SFT-everyday-conversations
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This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-360M](https://huggingface.co/HuggingFaceTB/SmolLM2-360M).
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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="lewtun/SmolLM2-360M-SFT-everyday-conversations", 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://lewtun-mlintern-smolsft1.hf.space?project=huggingface&runs=sft-smollm2-360m-everyday-conversations&sidebar=collapsed)
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This model was trained with SFT.
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### Framework versions
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- TRL: 1.3.0
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- Transformers: 5.7.0
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- Pytorch: 2.11.0
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- Datasets: 4.8.5
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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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