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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c038ada33664fc3c6178849a20ccf1d22dc09f4a63147b533f35ac2c80249b2
- Size of remote file:
- 358 kB
- SHA256:
- 71c4e517e6112e0b89452502923a4c502360d2973beacd5326d178a3d9690280
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