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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("deepmind/language-perceiver") model = AutoModelForMaskedLM.from_pretrained("deepmind/language-perceiver", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepmind/language-perceiver: direct link, hf CLI and curl.
- Browser
- Download file 805 MB
-
https://huggingface.co/deepmind/language-perceiver/resolve/1609e2ed9b466109014f29393a1359ff5a6a9ef3/pytorch_model.bin
- Command line
-
hf download hf://deepmind/language-perceiver@1609e2ed9b466109014f29393a1359ff5a6a9ef3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepmind/language-perceiver/resolve/1609e2ed9b466109014f29393a1359ff5a6a9ef3/pytorch_model.bin
805 MB
- Xet hash:
- 94a2c539bd9b53ce1281d080e1d953d69ca62bb518e63c485cdc5af767522c42
- Size of remote file:
- 805 MB
- SHA256:
- 405418b61079daa8780df29d31fa88cc8edb2e36ad2b53543c65fe0675df965b
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