Instructions to use melll-uff/bertweetbr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use melll-uff/bertweetbr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="melll-uff/bertweetbr")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("melll-uff/bertweetbr") model = AutoModelForMaskedLM.from_pretrained("melll-uff/bertweetbr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92024636adf881026445ec93b0f8cd47a4e719aadc6c4e58932406340ebbc693
- Size of remote file:
- 540 MB
- SHA256:
- 393a866893330cf2f57c0bf9f17bb4a576df3b50021c10bf40a63e34e66a74f6
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