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): 182463e
Update config.json
Browse files- config.json +1 -0
config.json
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.17.0.dev0",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"mask_token_id": 50264,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.17.0.dev0",
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