Text Classification
Transformers
Safetensors
English
Portuguese
deberta-v2
biology
science
nlp
biomedical
filter
deberta
text-embeddings-inference
Instructions to use Madras1/DebertaBioClass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Madras1/DebertaBioClass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Madras1/DebertaBioClass")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Madras1/DebertaBioClass") model = AutoModelForSequenceClassification.from_pretrained("Madras1/DebertaBioClass") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 355b02ce6311e902dc3e6ecd5cc347405509f2eabab5d5fc2bb168510c2f6cb6
- Size of remote file:
- 1.48 GB
- SHA256:
- 643443d882d0f6080357d9857b424735d58eec2550d13376a3f2ecbd48d7e638
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