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:
- dabaca20236a73a525349067e37707af0a4490017eb827754103b4a872936394
- Size of remote file:
- 14.2 kB
- SHA256:
- 7f275eaf89aea104b177803f419d489f5ae45869c6d78b55be22044ab060c0a8
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