Instructions to use azizmatin/llama3.2-1B-persianQAV2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use azizmatin/llama3.2-1B-persianQAV2.0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B-Instruct") model = PeftModel.from_pretrained(base_model, "azizmatin/llama3.2-1B-persianQAV2.0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e67ad6c4c8f8846c54b8042d903b561f64131c44336ebf1e8ce91a5d0a42bf7e
- Size of remote file:
- 5.56 kB
- SHA256:
- b630455499d7c37d20bbea7aabaedc4e0ab714a897cb2c65da91356d188776b2
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