Instructions to use daniel40/f07619e1-553f-4d9b-83d3-4ef6a13994db with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use daniel40/f07619e1-553f-4d9b-83d3-4ef6a13994db with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "daniel40/f07619e1-553f-4d9b-83d3-4ef6a13994db") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66abdf8e1bf7595c7c801c378d4cb7b961452a40918f0e3deecb1992772a4083
- Size of remote file:
- 84 MB
- SHA256:
- 4e4ec95aff08648ed9ea744056eca886e8ac041eda1fad2ad2c3b1bab2e1cb42
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