Instructions to use prxy5606/94d5efbe-a432-4669-840f-c14155c183bd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prxy5606/94d5efbe-a432-4669-840f-c14155c183bd with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("The-matt/llama2_ko-7b_distinctive-snowflake-182_1060") model = PeftModel.from_pretrained(base_model, "prxy5606/94d5efbe-a432-4669-840f-c14155c183bd") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from prxy5606/94d5efbe-a432-4669-840f-c14155c183bd: direct link, hf CLI and curl.
- Browser
- Download file 325 MB
-
https://huggingface.co/prxy5606/94d5efbe-a432-4669-840f-c14155c183bd/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://prxy5606/94d5efbe-a432-4669-840f-c14155c183bd/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/prxy5606/94d5efbe-a432-4669-840f-c14155c183bd/resolve/main/last-checkpoint/optimizer.pt
325 MB
- Xet hash:
- de18c65ad22ef2e6c5da1acc93c50458ff70e2fdcb4d3be758a9041c8b71a51a
- Size of remote file:
- 325 MB
- SHA256:
- 47bc2eedd646997c29bf3476367f0d685c1dc42233ebad27a17d5fb4352251f7
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