Instructions to use aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("JackFram/llama-160m") model = PeftModel.from_pretrained(base_model, "aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/rng_state.pth from aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c/resolve/main/last-checkpoint/rng_state.pth
- Command line
-
hf download hf://aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c/last-checkpoint/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c/resolve/main/last-checkpoint/rng_state.pth
14.2 kB
- Xet hash:
- e3145bb45b75811a21570734ddb283597678ccbba21c2b2adf8b97e4ec140487
- Size of remote file:
- 14.2 kB
- SHA256:
- b45701ef19a6a339cef80da5b14f611b61f55d0d4a9a895627886bb66d134fac
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