Instructions to use Lmprato/Euclid-Project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Lmprato/Euclid-Project with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "Lmprato/Euclid-Project") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2502/optimizer.pt from Lmprato/Euclid-Project: direct link, hf CLI and curl.
- Browser
- Download file 27.4 MB
-
https://huggingface.co/Lmprato/Euclid-Project/resolve/main/checkpoint-2502/optimizer.pt
- Command line
-
hf download hf://Lmprato/Euclid-Project/checkpoint-2502/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Lmprato/Euclid-Project/resolve/main/checkpoint-2502/optimizer.pt
27.4 MB
- Xet hash:
- dc6c00ef6d235de769c057b5c2270d2c1021957186c573d80d01b8a68a40fc13
- Size of remote file:
- 27.4 MB
- SHA256:
- f29745d74d4b5d8e1f6f1e280490c87054185935559a9d7ecd9ad5f6f13990b3
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