Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use felipe-nextly/text-classification-medical with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use felipe-nextly/text-classification-medical with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="felipe-nextly/text-classification-medical")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("felipe-nextly/text-classification-medical") model = AutoModelForSequenceClassification.from_pretrained("felipe-nextly/text-classification-medical", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b577f660303b5001403584159dc45364ab6f329a54d05e468612ca7e0a32f5d9
- Size of remote file:
- 4.73 kB
- SHA256:
- f3fc23d4a5906370e952b926e9137a6f52231ffcb69ad753b65baaf8aaf7b2de
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