Instructions to use facebook/w2v-bert-2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/w2v-bert-2.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/w2v-bert-2.0")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("facebook/w2v-bert-2.0") model = AutoModel.from_pretrained("facebook/w2v-bert-2.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -181,4 +181,4 @@ seqs, padding_mask = get_seqs_and_padding_mask(src)
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with torch.inference_mode():
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seqs, padding_mask = model.encoder_frontend(seqs, padding_mask)
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seqs, padding_mask = model.encoder(seqs, padding_mask)
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```
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with torch.inference_mode():
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seqs, padding_mask = model.encoder_frontend(seqs, padding_mask)
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seqs, padding_mask = model.encoder(seqs, padding_mask)
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```
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