Instructions to use akameswa/mistral-7b-instruct-code-16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akameswa/mistral-7b-instruct-code-16bit with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("akameswa/mistral-7b-instruct-code-16bit", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use akameswa/mistral-7b-instruct-code-16bit with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for akameswa/mistral-7b-instruct-code-16bit to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for akameswa/mistral-7b-instruct-code-16bit to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for akameswa/mistral-7b-instruct-code-16bit to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="akameswa/mistral-7b-instruct-code-16bit", max_seq_length=2048, )
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README.md
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- **Developed by:** akameswa
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- **License:** apache-2.0
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- **Finetuned from model :** unsloth/mistral-7b-instruct-v0.2-bnb-4bit
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This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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- **Developed by:** akameswa
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- **License:** apache-2.0
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- **Finetuned from model :** unsloth/mistral-7b-instruct-v0.2-bnb-4bit
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- **Finetuned on :** Java, Javascript, Python, C++
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- **Dataset :** codeparrot/xlcost-text-to-code
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This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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