Instructions to use hf-internal-testing/tiny-random-DistilBertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DistilBertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-DistilBertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DistilBertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-DistilBertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d13ef466a1c6233deb267c981c35896e72fe613451bc48fb94ddeaa7c88053e7
- Size of remote file:
- 365 kB
- SHA256:
- 2629b0ef8b3188551940c10d872b5679d466aa2e0af13fdd5635378f89360f59
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