Instructions to use gotzmann/1SV71 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gotzmann/1SV71 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/1SV71") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2700/optimizer.bin from gotzmann/1SV71: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/gotzmann/1SV71/resolve/main/checkpoint-2700/optimizer.bin
- Command line
-
hf download hf://gotzmann/1SV71/checkpoint-2700/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/gotzmann/1SV71/resolve/main/checkpoint-2700/optimizer.bin
1.34 GB
- Xet hash:
- 5ee8027c4423f708a28f48173b18f2ff708d13509fd2e0210732ad23d3316c3d
- Size of remote file:
- 1.34 GB
- SHA256:
- 1848476606f250811b6ae3eb58fd39d12e91173743ee91e0a61c50a9dadd6dc6
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