Instructions to use prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5 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, "prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5: direct link, hf CLI and curl.
- Browser
- Download file 151 kB
-
https://huggingface.co/prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5/resolve/main/last-checkpoint/optimizer.pt
151 kB
- Xet hash:
- f71d9120e1d68e116c2eda26f7d0737dc48b0b17b18d05077ad58b9942756d59
- Size of remote file:
- 151 kB
- SHA256:
- 071ad592fc68a96d8c1aae2178ecd2434e9ae2f7cf3598cf7ff631870f87e9ea
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