Instructions to use kernelguardian/llama2action with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kernelguardian/llama2action with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyPixel/Llama-2-7B-bf16-sharded") model = PeftModel.from_pretrained(base_model, "kernelguardian/llama2action") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe4fb28ff7cbc3c47d22f721496fe599ffa455aa36396662d67d6bea81a6caa5
- Size of remote file:
- 134 MB
- SHA256:
- d27a3baf4e2312d527c397c652ca2668830b13dc3e6ec5d2374066c1aa77ac32
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