Text Classification
Transformers
PyTorch
Safetensors
English
roberta
argument-mining
opinion-mining
information-extraction
inference-extraction
Twitter
Instructions to use TomatenMarc/TACO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TomatenMarc/TACO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TomatenMarc/TACO")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TomatenMarc/TACO") model = AutoModelForSequenceClassification.from_pretrained("TomatenMarc/TACO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcfed1b0dc0cc8e50193cd7d3ed53a96b31e28be65461bd787210ba653704a70
- Size of remote file:
- 3.2 kB
- SHA256:
- eb8e68af90bd93faab831a5666ee353336ee96fd6f70a8c18fc486f51acbd20f
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