Instructions to use dada22231/1b8ab1e0-6218-4b84-9c24-f74892620058 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/1b8ab1e0-6218-4b84-9c24-f74892620058 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-1.5B") model = PeftModel.from_pretrained(base_model, "dada22231/1b8ab1e0-6218-4b84-9c24-f74892620058") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2081e7ac8921f2f3cda0bf1bec3d5e2349236a89b0d9dcee1a545068885a2764
- Size of remote file:
- 148 MB
- SHA256:
- 956a775cce4e0817fb05c3e94c008317fe45239e2ad939de2b12820a1a131f37
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