Instructions to use thangla01/d39c2c44-497a-4263-b4dd-0b4ec14c1b5c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thangla01/d39c2c44-497a-4263-b4dd-0b4ec14c1b5c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-3B-Instruct") model = PeftModel.from_pretrained(base_model, "thangla01/d39c2c44-497a-4263-b4dd-0b4ec14c1b5c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54a316fc798a53eca5fca3c0bfc4e04e9abe2a2c5363aa3772f1cca35a99d7d1
- Size of remote file:
- 120 MB
- SHA256:
- e446711e9175e571ad8027d1ef96e1ec8529c911252e0b3bfad74d9627758c63
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