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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7ecdaa6f1b048d75404af47b40a8a02b9c0ff19793f044f94c4df4759fce4f5
- Size of remote file:
- 499 MB
- SHA256:
- 535c472d25776fd934de97a7032f8210b718dbc92d353fb80ba301ac04a0c4df
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