Instructions to use Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("katuni4ka/tiny-random-olmo-hf") model = PeftModel.from_pretrained(base_model, "Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/rng_state.pth from Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a/resolve/main/last-checkpoint/rng_state.pth
- Command line
-
hf download hf://Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a/last-checkpoint/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a/resolve/main/last-checkpoint/rng_state.pth
14.2 kB
- Xet hash:
- 9acde80a8ef3666c899ab5b0e03305014536962dcf0e6dc9e0db949111ea97e7
- Size of remote file:
- 14.2 kB
- SHA256:
- c12066a9c624fe38430ff3feea2dc6451e9f1a920255c11680c737a33d2c53a0
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