Instructions to use arj9719/robertuito_topic_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arj9719/robertuito_topic_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="arj9719/robertuito_topic_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("arj9719/robertuito_topic_classification") model = AutoModelForSequenceClassification.from_pretrained("arj9719/robertuito_topic_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from arj9719/robertuito_topic_classification: direct link, hf CLI and curl.
- Browser
- Download file 103 Bytes
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https://huggingface.co/arj9719/robertuito_topic_classification/resolve/main/README.md
- Command line
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hf download hf://arj9719/robertuito_topic_classification/README.md
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curl -L -o README.md https://huggingface.co/arj9719/robertuito_topic_classification/resolve/main/README.md
103 Bytes
| language: | |
| - es | |
| metrics: | |
| - accuracy | |
| library_name: transformers | |
| pipeline_tag: text-classification | |