Instructions to use lhong4759/44c7b55c-2c88-4fba-b98e-a22f2babdbc3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lhong4759/44c7b55c-2c88-4fba-b98e-a22f2babdbc3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama") model = PeftModel.from_pretrained(base_model, "lhong4759/44c7b55c-2c88-4fba-b98e-a22f2babdbc3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f85f05ced676a88484e2a17b69313af2d9cfe89803ae2c4a5e005b46a61b276
- Size of remote file:
- 25.3 MB
- SHA256:
- a2383c7dcb81e48825df94c102671216c74c27a2ed9d590a34a4e5e0bbeba238
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