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-4500/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-4500/optimizer.bin
- Command line
-
hf download hf://gotzmann/1OV77/checkpoint-4500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/gotzmann/1OV77/resolve/main/checkpoint-4500/optimizer.bin
1.34 GB
- Xet hash:
- 9dabf5dddd10dbd14297c10f5dd8af069cc793946c8e7b71b7a50cb60d7a95c3
- Size of remote file:
- 1.34 GB
- SHA256:
- f3a53e090a90653cecf9d610fc8af03f34d64601632ed086caf45224030bd6e6
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