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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b6020790509f7f9b2e7dcf2c04d7d2736b2f34529c5e22590c2b9f7b2f7af61
- Size of remote file:
- 341 kB
- SHA256:
- 260f62607d43f240bf670365a3f49c0ff34156f5d22b87c8c6e52afb364e693e
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