Text Classification
Transformers
Safetensors
English
Portuguese
roberta
biology
science
nlp
biomedical
filter
medical
text-embeddings-inference
Instructions to use Madras1/RobertaBioClass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Madras1/RobertaBioClass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Madras1/RobertaBioClass")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Madras1/RobertaBioClass") model = AutoModelForSequenceClassification.from_pretrained("Madras1/RobertaBioClass") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- f1
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- accuracy
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- recall
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base_model: roberta-base
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widget:
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- text: The mitochondria is the powerhouse of the cell and generates ATP.
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- f1
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- accuracy
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- recall
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datasets:
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- Madras1/BioClass80k
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base_model: roberta-base
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widget:
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- text: The mitochondria is the powerhouse of the cell and generates ATP.
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