Instructions to use hf-internal-testing/tiny-random-language_perceiver with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-language_perceiver with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-language_perceiver")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-language_perceiver") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-language_perceiver") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 655b8630ead1b551d960f6611a1a5b42d3553685d14b41b7a57933d560b9baf7
- Size of remote file:
- 462 kB
- SHA256:
- 384f9343dc0bebc2d4016dc7be6636d013f9d69292453ce2613168e70916c5d8
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