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base_model: google/gemma-4-E2B
library_name: peft
model_name: gemma4-code-assistant
tags:
- base_model:adapter:google/gemma-4-E2B
- lora
- sft
- transformers
- trl
licence: license
pipeline_tag: text-generation
---
# Model Card for gemma4-code-assistant
This model is a fine-tuned version of [google/gemma-4-E2B](https://huggingface.co/google/gemma-4-E2B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## 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
- PEFT 0.18.1
- TRL: 1.0.0
- Transformers: 5.6.0.dev0
- Pytorch: 2.10.0+cu128
- Datasets: 4.8.4
- 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}
}
``` |