Instructions to use goumbalamm/EsperBERTo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use goumbalamm/EsperBERTo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="goumbalamm/EsperBERTo")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("goumbalamm/EsperBERTo") model = AutoModelForMaskedLM.from_pretrained("goumbalamm/EsperBERTo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e81b6c7a69c8936e2b16151b0a02d27b34fc14efcf8301c17242ef179af9a428
- Size of remote file:
- 334 MB
- SHA256:
- 5488837d555ba98e98dced4bacf1210718f75b47bde051ac64b61c81cd6c8518
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