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:
- 5cb933cf49f4e338fdb88690c7c34718da441772c79e9dccb7bfab1654bf08ff
- Size of remote file:
- 6.71 kB
- SHA256:
- 8260439c5a50fc8af35f08ec44698ab45bd7df51e9a9f97c85ef746a7fdcb823
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