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
Commit ·
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Parent(s): ee6bd36
Update config.json
Browse files- config.json +1 -1
config.json
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265,
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"tokenizer_class": "RobertaTokenizer"
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}
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265,
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"tokenizer_class": "RobertaTokenizer"
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}
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