Instructions to use hf-internal-testing/tiny-random-PerceiverForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PerceiverForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-PerceiverForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PerceiverForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-PerceiverForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc1bda73e2416c1e44133fa066ef3d8efa572420eb6d96b8ff0340a2745b7795
- Size of remote file:
- 9.22 MB
- SHA256:
- 794a11dcc3b01625923f3ec8a181cb40514f934a1c2df9f54abbe1853ce3390c
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