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:
- b32d5eab6eb960e8eb05053c6a1a3132df8925511a425bc47189d59bb6b54fb9
- Size of remote file:
- 979 kB
- SHA256:
- 173cc0eca2aedadf9e3c5431823926ff16f5a93b6e1a6e7e9cba4fa3f1220909
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