Instructions to use deepmind/language-perceiver with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepmind/language-perceiver with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="deepmind/language-perceiver")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("deepmind/language-perceiver") model = AutoModelForMaskedLM.from_pretrained("deepmind/language-perceiver") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c402db4b17c8030ec3acd2d62eef14c6a45b492f82a8444a91091b065fb16d30
- Size of remote file:
- 805 MB
- SHA256:
- 941759e1c7489c5ffc7a922551a29e93581868972007aed48ae40e4a525ecba7
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