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
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Download README.md from FirstPotatoCoder/BacII-LoRA: direct link, hf CLI and curl.
- Browser
- Download file 587 Bytes
-
https://huggingface.co/FirstPotatoCoder/BacII-LoRA/resolve/main/README.md
- Command line
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hf download hf://FirstPotatoCoder/BacII-LoRA/README.md
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curl -L -o README.md https://huggingface.co/FirstPotatoCoder/BacII-LoRA/resolve/main/README.md
587 Bytes
metadata
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
