Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use Humberto/MedicalArticlesClassificationModelMultiLabel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Humberto/MedicalArticlesClassificationModelMultiLabel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Humberto/MedicalArticlesClassificationModelMultiLabel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Humberto/MedicalArticlesClassificationModelMultiLabel") model = AutoModelForSequenceClassification.from_pretrained("Humberto/MedicalArticlesClassificationModelMultiLabel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Training in progress epoch 2
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Training in progress epoch 1
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Training in progress epoch 0
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Training in progress epoch 2
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Training in progress epoch 1
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Training in progress epoch 0
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initial commit
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