Instructions to use hashk1/EsperBERTo-malgranda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hashk1/EsperBERTo-malgranda with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hashk1/EsperBERTo-malgranda")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hashk1/EsperBERTo-malgranda") model = AutoModelForMaskedLM.from_pretrained("hashk1/EsperBERTo-malgranda") - Notebooks
- Google Colab
- Kaggle
Commit History
upload flax model 7cd86a3
allow flax 4fad17f
Update README.md de59cfe
Update README.md bbb0709
Create README.md e2c8fb3
commit from hashk1 9875028
hashk1 commited on