Transformers
Safetensors
English
text-generation-inference
unsloth
mixtral
mixture-of-experts
qlora
code-generation
python-coder
code-alpaca
Instructions to use Puxis97/Mixtral-8x7B-Python-Coder-CodeAlpaca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Puxis97/Mixtral-8x7B-Python-Coder-CodeAlpaca with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Puxis97/Mixtral-8x7B-Python-Coder-CodeAlpaca", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
metadata
base_model: mistralai/Mixtral-8x7B-Instruct-v0.1
tags:
- text-generation-inference
- transformers
- unsloth
- mixtral
- mixture-of-experts
- qlora
- code-generation
- python-coder
- code-alpaca
license: apache-2.0
language:
- en
Puxis97/Mixtral-8x7B-Python-Coder-CodeAlpaca ๐
This model is a Mixtral 8x7B Instruct model fine-tuned using QLoRA on the CodeAlpaca 20K dataset to specialize in Python code instruction following and generation.
- Developed by: Puxis97
- License: apache-2.0
- Finetuned from model : mistralai/Mixtral-8x7B-Instruct-v0.1
Training Details
This fine-tuned model was built for high-efficiency using Unsloth's QLoRA optimizations and the Hugging Face TRL library, resulting in a powerful, instruction-following code generation model that runs on consumer GPUs.
| Setting | Value |
|---|---|
| Base Model | mistralai/Mixtral-8x7B-Instruct-v0.1 |
| Dataset | HuggingFaceH4/CodeAlpaca_20K |
| Method | QLoRA (4-bit quantization) |
| Task | Code Instruction Following / Python Coding |
