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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("melll-uff/bertweetbr") model = AutoModelForMaskedLM.from_pretrained("melll-uff/bertweetbr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from melll-uff/bertweetbr: direct link, hf CLI and curl.
- Browser
- Download file 540 MB
-
https://huggingface.co/melll-uff/bertweetbr/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://melll-uff/bertweetbr@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/melll-uff/bertweetbr/resolve/refs%2Fpr%2F2/pytorch_model.bin
540 MB
- Xet hash:
- 92024636adf881026445ec93b0f8cd47a4e719aadc6c4e58932406340ebbc693
- Size of remote file:
- 540 MB
- SHA256:
- 393a866893330cf2f57c0bf9f17bb4a576df3b50021c10bf40a63e34e66a74f6
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