Instructions to use Isma/v2_80k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isma/v2_80k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Isma/v2_80k")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Isma/v2_80k") model = AutoModel.from_pretrained("Isma/v2_80k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22581245c978054e734d2d945b1d2c6e0219760ba6ff089863cb8c9610cb3933
- Size of remote file:
- 378 MB
- SHA256:
- 54d8f8b8660bfac60def5a5030e2bedadd854e9566e1de1f1fd6d531f0fa1c5c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.