Xiaolihai/qwen-3b-medical-classifier

Qwen 3B Medical Department Classifier

This is a fine-tuned Qwen 3B model for medical department classification on Chinese medical dialogues.

Model Details

• Base Model: Qwen 3B
• Task: Medical Department Classification
• Language: Chinese (zh)
• Number of Classes: 44
• Classes: ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34', '35', '36', '37', '38', '39', '40', '41', '42', '43']

Model Description

This model has been fine-tuned to classify medical dialogues into appropriate medical departments. It's based on the Qwen 3B model and has been specifically trained for Chinese medical text classification.

Usage

from transformers import AutoModelForSequenceClassification, AutoTokenizer

# Load model and tokenizer
model = AutoModelForSequenceClassification.from_pretrained("Xiaolihai/qwen-3b-medical-classifier")
tokenizer = AutoTokenizer.from_pretrained("Xiaolihai/qwen-3b-medical-classifier")

# Example usage
text = "患者描述胸痛症状，需要进一步检查"
inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
outputs = model(**inputs)
predictions = outputs.logits.argmax(dim=-1)

Training

The model was fine-tuned on medical dialogue data with 400 training samples.

License

This model is released under the MIT License.