Instructions to use mrHungddddh/72f770ce-5c1d-4442-8b76-29e05e66a77d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mrHungddddh/72f770ce-5c1d-4442-8b76-29e05e66a77d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-1B") model = PeftModel.from_pretrained(base_model, "mrHungddddh/72f770ce-5c1d-4442-8b76-29e05e66a77d") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ccbf6bcf211629b06e3d60597503f2fef4d1a8e25906ec67369438b3c0f31d5
- Size of remote file:
- 22.6 MB
- SHA256:
- 7438a63e75bf00585c324defd18038d11e37459c1a908aec05d62da0b62c2ae4
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