Instructions to use K00B404/llama3_8B_python_tuned_90steps_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use K00B404/llama3_8B_python_tuned_90steps_lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("K00B404/llama3_8B_python_tuned_90steps_lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use K00B404/llama3_8B_python_tuned_90steps_lora 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 K00B404/llama3_8B_python_tuned_90steps_lora 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 K00B404/llama3_8B_python_tuned_90steps_lora to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for K00B404/llama3_8B_python_tuned_90steps_lora to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="K00B404/llama3_8B_python_tuned_90steps_lora", max_seq_length=2048, )
- Xet hash:
- f337d447ab4f85088b61d27c1ebe15fc7cb026175a050ce218005232e926b869
- Size of remote file:
- 168 MB
- SHA256:
- 525a15938d549b79d8d41cc1773b7763d8514df217750f4f84b919ea898739b7
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