Instructions to use hf-tiny-model-private/tiny-random-YosoForMaskedLM 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-YosoForMaskedLM 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-YosoForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-YosoForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-YosoForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bd3fd839ed18f32473b4addedd6a426018ffa44f7fb13d67b67c63d08ff5185
- Size of remote file:
- 377 kB
- SHA256:
- f1d07c46b928d1a743f3f0daaab5bdec5a0f3a51b8323410224b5fcffbac4a3e
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