Instructions to use selectorseb/selector_function_calling_llama8b_3.1_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selectorseb/selector_function_calling_llama8b_3.1_final with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("selectorseb/selector_function_calling_llama8b_3.1_final", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use selectorseb/selector_function_calling_llama8b_3.1_final 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 selectorseb/selector_function_calling_llama8b_3.1_final 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 selectorseb/selector_function_calling_llama8b_3.1_final to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for selectorseb/selector_function_calling_llama8b_3.1_final to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="selectorseb/selector_function_calling_llama8b_3.1_final", max_seq_length=2048, )
- Xet hash:
- c03b5005add58699bc384baa4e4c0acd84315b6f9b091df3eae6c66a07181cb8
- Size of remote file:
- 83.9 MB
- SHA256:
- 365aa1840e76e70088d479bfa6092ef6886e2fbe4405d0b32fb95fa7a3a144a0
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