Instructions to use cimol/566be688-333f-4f40-961d-7b85f6a1352a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/566be688-333f-4f40-961d-7b85f6a1352a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-random-GemmaForCausalLM") model = PeftModel.from_pretrained(base_model, "cimol/566be688-333f-4f40-961d-7b85f6a1352a") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from cimol/566be688-333f-4f40-961d-7b85f6a1352a: direct link, hf CLI and curl.
- Browser
- Download file 76.7 kB
-
https://huggingface.co/cimol/566be688-333f-4f40-961d-7b85f6a1352a/resolve/main/adapter_model.bin
- Command line
-
hf download hf://cimol/566be688-333f-4f40-961d-7b85f6a1352a/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/cimol/566be688-333f-4f40-961d-7b85f6a1352a/resolve/main/adapter_model.bin
76.7 kB
- Xet hash:
- 0e96c88063f9e2a18e2feefc7f7459e32627f6c35bc7581a4d5fd0e2a3edb655
- Size of remote file:
- 76.7 kB
- SHA256:
- 0dcf7d465048b186afc3c8893ad2c688f737c55248075bd15d7d901d930bc5f8
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