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:
- d522fe699f80d7f97e8f0d800ea8a578d32d40234453893f6d7007422d9d4d4e
- Size of remote file:
- 6.78 kB
- SHA256:
- 64404af61dfa2c9087d3bf6c445c534115e2940054f31df281abec16df4b37f4
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