Instructions to use OpenNMT/Mistral-7B-v0.1-instruct-ct2-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenNMT/Mistral-7B-v0.1-instruct-ct2-int8 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenNMT/Mistral-7B-v0.1-instruct-ct2-int8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7164d938a8630c721db6048d5561154450bf4221f5ba586080937a45ec05edcb
- Size of remote file:
- 7.25 GB
- SHA256:
- 1244480c27ea1a9d23ee999c4c1466e8af1ba69a828c939e20e3e40113ea1c8d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.