Text Classification
Transformers
Safetensors
Portuguese
bert
Eval Results (legacy)
text-embeddings-inference
Instructions to use Silly-Machine/TuPy-Bert-Large-Multilabel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Silly-Machine/TuPy-Bert-Large-Multilabel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Silly-Machine/TuPy-Bert-Large-Multilabel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Silly-Machine/TuPy-Bert-Large-Multilabel") model = AutoModelForSequenceClassification.from_pretrained("Silly-Machine/TuPy-Bert-Large-Multilabel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Silly-Machine/TuPy-Bert-Large-Multilabel: direct link, hf CLI and curl.
- Browser
- Download file 678 kB
-
https://huggingface.co/Silly-Machine/TuPy-Bert-Large-Multilabel/resolve/a1d9df5ba47d3a8ace7e882cc06d168cf57dfd4e/tokenizer.json
- Command line
-
hf download hf://Silly-Machine/TuPy-Bert-Large-Multilabel@a1d9df5ba47d3a8ace7e882cc06d168cf57dfd4e/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Silly-Machine/TuPy-Bert-Large-Multilabel/resolve/a1d9df5ba47d3a8ace7e882cc06d168cf57dfd4e/tokenizer.json
678 kB
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