---
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
```