Instructions to use vulcan2506/Strategic-LLAMA-V1-InstructBase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vulcan2506/Strategic-LLAMA-V1-InstructBase with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vulcan2506/Strategic-LLAMA-V1-InstructBase", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use vulcan2506/Strategic-LLAMA-V1-InstructBase 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 vulcan2506/Strategic-LLAMA-V1-InstructBase 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 vulcan2506/Strategic-LLAMA-V1-InstructBase to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for vulcan2506/Strategic-LLAMA-V1-InstructBase to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="vulcan2506/Strategic-LLAMA-V1-InstructBase", max_seq_length=2048, )
- Xet hash:
- 51eafa2e83b1773a328cd477deb52831759349b948c8bf43eca28ee8b35635bd
- Size of remote file:
- 6.23 kB
- SHA256:
- 985c6d58f0541f2ba25df2a03d78d91002ef9ec5b987ff84c1fb65dbe2d116d6
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