Instructions to use Paladiso/8e6f4d68-0920-4b5c-8036-5bc83b2e08d4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Paladiso/8e6f4d68-0920-4b5c-8036-5bc83b2e08d4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/CodeLlama-7b-hf") model = PeftModel.from_pretrained(base_model, "Paladiso/8e6f4d68-0920-4b5c-8036-5bc83b2e08d4") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/rng_state.pth from Paladiso/8e6f4d68-0920-4b5c-8036-5bc83b2e08d4: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/Paladiso/8e6f4d68-0920-4b5c-8036-5bc83b2e08d4/resolve/main/last-checkpoint/rng_state.pth
- Command line
-
hf download hf://Paladiso/8e6f4d68-0920-4b5c-8036-5bc83b2e08d4/last-checkpoint/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/Paladiso/8e6f4d68-0920-4b5c-8036-5bc83b2e08d4/resolve/main/last-checkpoint/rng_state.pth
14.2 kB
- Xet hash:
- adb03c51de78c29cda8396a881f9799cf7ab5d2d24473c3767ffbec4756783d9
- Size of remote file:
- 14.2 kB
- SHA256:
- 2ca36859b3908db300a5d309a3c1a9aeaaf6c594159bb7a3710c3b55798d8e6b
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