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:
- 18ef33692df08ba81c03c574c1706990869a35380d09d48620eba519faa11989
- Size of remote file:
- 6.78 kB
- SHA256:
- 08d8355d8a6512be7ebf5a48918e756439c0f94a8ce40238c9ca82d6245d9379
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