Instructions to use facebook/data2vec-text-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/data2vec-text-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/data2vec-text-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("facebook/data2vec-text-base") model = AutoModel.from_pretrained("facebook/data2vec-text-base") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
2ab9480 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:65f2e9bc8b76d5bfe3be263ce6d3a05a248c2d1e954fbc4b26dc96f592d53df3
size 498876075
|