Instructions to use arvnoodle/hclcodegemma-7b-it-javascript-lotuscript with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arvnoodle/hclcodegemma-7b-it-javascript-lotuscript with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("arvnoodle/hclcodegemma-7b-it-javascript-lotuscript", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
metadata
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- gemma
- trl
base_model: unsloth/codegemma-7b-bnb-4bit
Uploaded model
- Developed by: arvnoodle
- License: apache-2.0
- Finetuned from model : unsloth/codegemma-7b-bnb-4bit
This gemma model was trained 2x faster with Unsloth and Huggingface's TRL library.
