Instructions to use error577/1d9b670c-b7d0-4ae4-99c8-d810dfdbf529 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use error577/1d9b670c-b7d0-4ae4-99c8-d810dfdbf529 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-135M-Instruct") model = PeftModel.from_pretrained(base_model, "error577/1d9b670c-b7d0-4ae4-99c8-d810dfdbf529") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from error577/1d9b670c-b7d0-4ae4-99c8-d810dfdbf529: direct link, hf CLI and curl.
- Browser
- Download file 39.1 MB
-
https://huggingface.co/error577/1d9b670c-b7d0-4ae4-99c8-d810dfdbf529/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://error577/1d9b670c-b7d0-4ae4-99c8-d810dfdbf529/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/error577/1d9b670c-b7d0-4ae4-99c8-d810dfdbf529/resolve/main/adapter_model.safetensors
39.1 MB
- Xet hash:
- c421c2f92538fea15babd9a1d6cbccb745051a4b3dbb3eaca9be3cde0e25b17d
- Size of remote file:
- 39.1 MB
- SHA256:
- 77c24ea96889fec96c59459d94d690091d935865f1a72637cfe9a78969e5da23
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