Instructions to use hf-internal-testing/tiny-random-EsmForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-EsmForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-EsmForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-EsmForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-EsmForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fd20919482e4f96c9f190403b90d724dea68b7899e2330625d897e167a7212d
- Size of remote file:
- 243 kB
- SHA256:
- 978693c571bfeb7e919a24e94fb31e4a52d6a82b0996a40167dda0f3f7f6e968
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