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:
- ec40e36dd53539be4529ce258a14ff43e39ad2b34f4884ab754b40af3a77d1ee
- Size of remote file:
- 997 MB
- SHA256:
- 6612d8b0060fcdf78cdf9ff40bf2cb9daf56679c80d1aa9aac8f470c10ae3bc6
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