Instructions to use vmpsergio/f3e6c8e0-4f8c-4f37-9fb9-199f1a99090c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vmpsergio/f3e6c8e0-4f8c-4f37-9fb9-199f1a99090c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-135M") model = PeftModel.from_pretrained(base_model, "vmpsergio/f3e6c8e0-4f8c-4f37-9fb9-199f1a99090c") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from vmpsergio/f3e6c8e0-4f8c-4f37-9fb9-199f1a99090c: direct link, hf CLI and curl.
- Browser
- Download file 19.7 MB
-
https://huggingface.co/vmpsergio/f3e6c8e0-4f8c-4f37-9fb9-199f1a99090c/resolve/a740c89a6be7b806e0bb76b94467a8486f25dca8/adapter_model.bin
- Command line
-
hf download hf://vmpsergio/f3e6c8e0-4f8c-4f37-9fb9-199f1a99090c@a740c89a6be7b806e0bb76b94467a8486f25dca8/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/vmpsergio/f3e6c8e0-4f8c-4f37-9fb9-199f1a99090c/resolve/a740c89a6be7b806e0bb76b94467a8486f25dca8/adapter_model.bin
19.7 MB
- Xet hash:
- e5554e32a4bea65aaae8e375dcb869ddceb4c821c931c5dd39d219e9969027aa
- Size of remote file:
- 19.7 MB
- SHA256:
- a93397a9b36f389eac171a37c8b36deb27303f44f17573f5a64fcdb4205561b1
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