Instructions to use FirstPotatoCoder/BacII-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FirstPotatoCoder/BacII-LoRA with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FirstPotatoCoder/BacII-LoRA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
File size: 587 Bytes
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base_model: unsloth/gemma-4-31B-it-unsloth-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- gemma4
- trl
license: apache-2.0
language:
- en
---
# Uploaded finetuned model
- **Developed by:** FirstPotatoCoder
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-4-31B-it-unsloth-bnb-4bit
This gemma4 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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