Instructions to use diagonalge/c4650a4d-c32d-4e0f-a27c-171ba40b07e6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use diagonalge/c4650a4d-c32d-4e0f-a27c-171ba40b07e6 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-1B-Instruct") model = PeftModel.from_pretrained(base_model, "diagonalge/c4650a4d-c32d-4e0f-a27c-171ba40b07e6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 55fa1fc70b678e81cc31cdebf7bd9b046adf3101ac51ff6935b51b283f5058fd
- Size of remote file:
- 45.1 MB
- SHA256:
- be97b6edf632530b581b1785612d77c06d017d9614ef490ffc2a998dbe2b9d3b
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