Instructions to use StellarCoffee/Llama-3.1-8b-Python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StellarCoffee/Llama-3.1-8b-Python with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("StellarCoffee/Llama-3.1-8b-Python", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use StellarCoffee/Llama-3.1-8b-Python 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 StellarCoffee/Llama-3.1-8b-Python 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 StellarCoffee/Llama-3.1-8b-Python to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for StellarCoffee/Llama-3.1-8b-Python to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="StellarCoffee/Llama-3.1-8b-Python", max_seq_length=2048, )
- Xet hash:
- d394694792b74b5e856bb39f305c8c8bdba4f53bc41ab0aa8cabcc5de9cfe7f9
- Size of remote file:
- 336 MB
- SHA256:
- a0ae7660819fbd57c1dbeaf651fe27d38a74e254131ebeeb2e671dfe59e7cc55
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.