Instructions to use gavrilstep/85aa9e5d-cbb6-4fe6-9e71-d69f333295b0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gavrilstep/85aa9e5d-cbb6-4fe6-9e71-d69f333295b0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Theta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "gavrilstep/85aa9e5d-cbb6-4fe6-9e71-d69f333295b0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5754c12e35541afc5ee14ac265bca99de07fc323e3c0f6b8922d4a152f3151e2
- Size of remote file:
- 2.27 GB
- SHA256:
- 01fd8b69d09a4c2d2e42f4101b036f2ce80fca7d674915c0ed497dbcfdc655fa
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