Instructions to use johngreendr1/01bc5f12-9c70-4cc8-92fa-e2a2634ea625 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use johngreendr1/01bc5f12-9c70-4cc8-92fa-e2a2634ea625 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B") model = PeftModel.from_pretrained(base_model, "johngreendr1/01bc5f12-9c70-4cc8-92fa-e2a2634ea625") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61ef173d33a870c102441c13b03d47a38131acd7d54e2d6b6a66a6e7c58c743c
- Size of remote file:
- 1.06 GB
- SHA256:
- 7d95ad14b1b6555f889fda4e9c2a98186c051a5417eeea94aa27e3c8eb1bbe3a
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