Instructions to use Weni/ZeroShot-Multilanguage-Zephyr-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Weni/ZeroShot-Multilanguage-Zephyr-7B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-alpha") model = PeftModel.from_pretrained(base_model, "Weni/ZeroShot-Multilanguage-Zephyr-7B") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2000/optimizer.pt from Weni/ZeroShot-Multilanguage-Zephyr-7B: direct link, hf CLI and curl.
- Browser
- Download file 218 MB
-
https://huggingface.co/Weni/ZeroShot-Multilanguage-Zephyr-7B/resolve/main/checkpoint-2000/optimizer.pt
- Command line
-
hf download hf://Weni/ZeroShot-Multilanguage-Zephyr-7B/checkpoint-2000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Weni/ZeroShot-Multilanguage-Zephyr-7B/resolve/main/checkpoint-2000/optimizer.pt
218 MB
- Xet hash:
- fe6091d9c794ab4f032e0784441586708289bda384c68e30e38137fd0f0863b1
- Size of remote file:
- 218 MB
- SHA256:
- 7ab952a56a11efbf26e6e24391caa55225a16526b8a6be1b4de3d267c0832af6
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