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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54c32c3b6c3f5f18e6b0f014e9f88f08f89f1459ab1866046b77b463bc5e278e
- Size of remote file:
- 804 MB
- SHA256:
- ab63f7d8b01201214a7760b67a8654cf467bcf1f6eddd341df0f89a195c37a27
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