Instructions to use gotzmann/1OV77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gotzmann/1OV77 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "gotzmann/1OV77") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-4815/optimizer.bin from gotzmann/1OV77: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/gotzmann/1OV77/resolve/main/checkpoint-4815/optimizer.bin
- Command line
-
hf download hf://gotzmann/1OV77/checkpoint-4815/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/gotzmann/1OV77/resolve/main/checkpoint-4815/optimizer.bin
1.34 GB
- Xet hash:
- 882d78fd21c79ea51530465839ec387dc1c2090fdc688939529bf449c591aebb
- Size of remote file:
- 1.34 GB
- SHA256:
- a0eac9a4ac012fa86b61d20a91197fda6d5ed01a2098b339d7ce8f9412d14a53
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