Instructions to use Zrald/GE-Mistral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Zrald/GE-Mistral with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Mistral-Nemo-Instruct-2407") model = PeftModel.from_pretrained(base_model, "Zrald/GE-Mistral") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Zrald/GE-Mistral: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/Zrald/GE-Mistral/resolve/main/tokenizer.json
- Command line
-
hf download hf://Zrald/GE-Mistral/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Zrald/GE-Mistral/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 183feaf3854ea652c1087520f20fdc39282f652edf10541e6904a3d3f975425e
- Size of remote file:
- 17.1 MB
- SHA256:
- b0240ce510f08e6c2041724e9043e33be9d251d1e4a4d94eb68cd47b954b61d2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.