Instructions to use hf-tiny-model-private/tiny-random-FunnelForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-FunnelForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-tiny-model-private/tiny-random-FunnelForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FunnelForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-FunnelForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e678480dde3164011038d4de59413a5aeb82e91e1ec03ce6d3ca9b475182d97
- Size of remote file:
- 319 kB
- SHA256:
- bd62b036b2886571038170e86ac910989fa753e455516dc99bb66e82d9f402de
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