Instructions to use Consensus/instructor-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Consensus/instructor-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Consensus/instructor-large") model = AutoModel.from_pretrained("Consensus/instructor-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Consensus/instructor-large: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/Consensus/instructor-large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Consensus/instructor-large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Consensus/instructor-large/resolve/main/pytorch_model.bin
1.34 GB
- Xet hash:
- 232e8527875674ff48eeb8e6b6a537c25e88c0057db240c78db7bf3759af219f
- Size of remote file:
- 1.34 GB
- SHA256:
- fb7f63752cf10103be938bc50dfad0b6fa1e63bc67b963471fc827838d9bbb41
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.