Instructions to use Paladiso/369db93c-b0b2-4862-895e-e55b2f44da91 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Paladiso/369db93c-b0b2-4862-895e-e55b2f44da91 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openlm-research/open_llama_3b") model = PeftModel.from_pretrained(base_model, "Paladiso/369db93c-b0b2-4862-895e-e55b2f44da91") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from Paladiso/369db93c-b0b2-4862-895e-e55b2f44da91: direct link, hf CLI and curl.
- Browser
- Download file 26.2 MB
-
https://huggingface.co/Paladiso/369db93c-b0b2-4862-895e-e55b2f44da91/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://Paladiso/369db93c-b0b2-4862-895e-e55b2f44da91/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Paladiso/369db93c-b0b2-4862-895e-e55b2f44da91/resolve/main/last-checkpoint/optimizer.pt
26.2 MB
- Xet hash:
- 68128e297d603c72579796c28b8a58b82c8ea6f54d8160c395d520f31143ff5a
- Size of remote file:
- 26.2 MB
- SHA256:
- aad983915af07282ec1dd45cf4ca883699361aa9ab653c1c571b42de8391e068
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