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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e9da7076122165d215b14dc6f12f0189b283f928f50c82ab593049da02ea231
- Size of remote file:
- 738 MB
- SHA256:
- 10700b5450c383cc2ef651fe5e32a955050319a1b62eb6a0d5a2193ed492f8a8
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