Instructions to use sgugger/esberto-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgugger/esberto-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sgugger/esberto-small")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sgugger/esberto-small") model = AutoModelForMaskedLM.from_pretrained("sgugger/esberto-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ea1709cd391189bdb104d53ee69c81290e740dd03adbfd91b84d83402e7150a
- Size of remote file:
- 2.61 kB
- SHA256:
- 03a22f2c6017d925d661265455439b9fe78e0e4b1b0fa15bd35c1c03f48f8cde
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