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license: mit
library_name: transformers
pipeline_tag: text-classification
tags:
- medical
- text-classification
- distilbert
---
# Medical Text Classifier
This model classifies text as medical or non-medical using DistilBERT.
## Usage
```python
from transformers import DistilBertTokenizer, DistilBertForSequenceClassification
tokenizer = DistilBertTokenizer.from_pretrained("PSSSSA/classifierctmodel")
model = DistilBertForSequenceClassification.from_pretrained("PSSSSA/classifierctmodel")
```
### Step 3: Wait and Check Again
After updating the README:
1. **Wait 5-10 minutes** for Hugging Face to process
2. **Refresh your model page**
3. **Look for the inference widget**
### Step 4: Alternative - Test with curl
Try this curl command to see the raw response:
```bash
curl -X POST \
-H "Authorization: Bearer API" \
-H "Content-Type: application/json" \
-d '{"inputs": "I have a headache"}' \
https://api-inference.huggingface.co/models/PSSSSA/classifierctmodel
``` |