Instructions to use trangtrannnnn/00587261-1c3d-457a-85df-fba8eb32bd8d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trangtrannnnn/00587261-1c3d-457a-85df-fba8eb32bd8d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-1.7B") model = PeftModel.from_pretrained(base_model, "trangtrannnnn/00587261-1c3d-457a-85df-fba8eb32bd8d") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from trangtrannnnn/00587261-1c3d-457a-85df-fba8eb32bd8d: direct link, hf CLI and curl.
- Browser
- Download file 36.3 MB
-
https://huggingface.co/trangtrannnnn/00587261-1c3d-457a-85df-fba8eb32bd8d/resolve/main/adapter_model.bin
- Command line
-
hf download hf://trangtrannnnn/00587261-1c3d-457a-85df-fba8eb32bd8d/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/trangtrannnnn/00587261-1c3d-457a-85df-fba8eb32bd8d/resolve/main/adapter_model.bin
36.3 MB
- Xet hash:
- b3a15a7e43b9768c01bf1adc0641c2b3c544838842e5cf23d31ddc8a061a2d05
- Size of remote file:
- 36.3 MB
- SHA256:
- 469c9aadda183bcb8d94b3e5d0e183ad7d51db83db7110f52590e1b528534c68
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