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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("facebook/data2vec-text-base") model = AutoModel.from_pretrained("facebook/data2vec-text-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
bd0db19 -
Update README.md
f0e7dae -
Update config.json
7a36806 -
Update README.md
ca39186 -
Update config.json
fe3d5c1 -
Update config.json
ee6bd36 -
Update config.json
57e56fe -
Create README.md
182463e
-
add model
2ab9480 -
initial commit
4054fc3