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:
- ca17ec272885244dbd28c019b5a8ad15184c9574601747a1d73fc62a25a22c45
- Size of remote file:
- 573 kB
- SHA256:
- 808fbfcac37d9c5d5ca373b0568764755419f9d6b15a29f80bc675e7179e4fc6
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