Instructions to use dimasik2987/ee18d753-a67f-44fb-bd48-52c33d7962f4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik2987/ee18d753-a67f-44fb-bd48-52c33d7962f4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("JackFram/llama-160m") model = PeftModel.from_pretrained(base_model, "dimasik2987/ee18d753-a67f-44fb-bd48-52c33d7962f4") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/rng_state.pth from dimasik2987/ee18d753-a67f-44fb-bd48-52c33d7962f4: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/dimasik2987/ee18d753-a67f-44fb-bd48-52c33d7962f4/resolve/main/last-checkpoint/rng_state.pth
- Command line
-
hf download hf://dimasik2987/ee18d753-a67f-44fb-bd48-52c33d7962f4/last-checkpoint/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/dimasik2987/ee18d753-a67f-44fb-bd48-52c33d7962f4/resolve/main/last-checkpoint/rng_state.pth
14.2 kB
- Xet hash:
- 3890a296ec979794e7b34500379cad2db565af92a6e27e2b8e2bc81eb2a2a428
- Size of remote file:
- 14.2 kB
- SHA256:
- 9e651d14e7ee52a338fd24cd91e6b6490d38a4418546e878a83bea1f77d0d566
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