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", device_map="auto")# 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:
- 5dddf2cf94adc18099defebd87b3707cc38a60b484e1493932df843c7cfd7b25
- Size of remote file:
- 224 kB
- SHA256:
- 0ee25165925e29468c77b0535eb1c3067efe1aad51f4d9864a486c9adce87562
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