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smollm2-1.7b-SFT/README.md
ModelHub XC 75fb84c1f4 初始化项目,由ModelHub XC社区提供模型
Model: jdebaer/smollm2-1.7b-SFT
Source: Original Platform
2026-06-12 16:14:30 +08:00

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---
base_model: HuggingFaceTB/SmolLM2-1.7B
library_name: transformers
model_name: output
tags:
- generated_from_trainer
- trl
- sft
licence: license
license: apache-2.0
---
# Model Card for output
This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-1.7B](https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B).
It has been trained for one epoch using the training samples from [TRL](https://github.com/huggingface/trl) that comprise less than or equal to 1024 tokens after applying the chat template (+600k samples).
## Quick start
```python
from transformers import pipeline
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?"
generator = pipeline("text-generation", model="None", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```
## Training procedure
This model was trained with SFT.
### Framework versions
- TRL: 0.29.1
- Transformers: 5.2.0
- Pytorch: 2.10.0+cu128
- Datasets: 4.6.1
- Tokenizers: 0.22.2
## Citations
Cite TRL as:
```bibtex
@software{vonwerra2020trl,
title = {{TRL: Transformers Reinforcement Learning}},
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},
license = {Apache-2.0},
url = {https://github.com/huggingface/trl},
year = {2020}
}
```