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")# pip install -U transformers accelerate # 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
Fix placeholder text and missing dataset name in model card
#1
by BananaMindBot - opened
The model card contains several instances of 'More information needed' and refers to the dataset as 'None'. I have removed the placeholder sections and corrected the dataset reference to 'medical' (inferred from the model name) to make the card more professional and informative. I also removed the auto-generated comment.
Opened automatically by BananaMindBot. Close it if it is not useful - no hard feelings.