Instructions to use gotzmann/1JV42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gotzmann/1JV42 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/1JV42") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download checkpoint-3000/optimizer.pt from gotzmann/1JV42: direct link, hf CLI and curl.
- Browser
- Download file 2.01 GB
-
https://huggingface.co/gotzmann/1JV42/resolve/main/checkpoint-3000/optimizer.pt
- Command line
-
hf download hf://gotzmann/1JV42/checkpoint-3000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/gotzmann/1JV42/resolve/main/checkpoint-3000/optimizer.pt
2.01 GB
- Xet hash:
- 5b721d0fc186227d1d49083b690ee64d58847bfca559bbab34563db567946277
- Size of remote file:
- 2.01 GB
- SHA256:
- e39b7c62555ae310b456e00b4e7b6249d5070eded0cce44b1f0694d8a09d69cb
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