Instructions to use hf-internal-testing/tiny-random-YosoForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-YosoForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-YosoForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-YosoForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-YosoForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b33da4a0e582702d041dd0f507dc8df048e16c9fbd2304ebd51a96d6efb3b04
- Size of remote file:
- 377 kB
- SHA256:
- 6c6f314e8f64067279989d2178a3f93bb088420c1f7cf997f596c4a9865979d9
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