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:
- 65650e089420440fc12c1de105314cf4d424ba4ccafc6ca387c0e7aaf29f49e6
- Size of remote file:
- 334 MB
- SHA256:
- f4e1dcfb7883a373776798818e25196183eaf0a2ff10e0b6a8cd84bb0de08cf3
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