Instructions to use hf-internal-testing/tiny-random-MPNetForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MPNetForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-MPNetForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MPNetForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-MPNetForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ac53382d444d4876c3e77cc965a4972e2123f5d37ab4cc760100cc4cfd90d43
- Size of remote file:
- 1.51 MB
- SHA256:
- f8e9852b292597f1d46f260956043bed2ec5ec6aa2ad99448fd9eeeee043dbbd
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