| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| MODEL_PATH = "lzw1008/ConspEmoLLM-v2" | |
| tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH) | |
| model = AutoModelForCausalLM.from_pretrained(MODEL_PATH) | |
| def classify_conspiracy(text): | |
| prompt = f"""Human: | |
| Task: Classify the text regarding conspiracy theories or misinformation. | |
| Text: {text} | |
| Assistant: | |
| """ | |
| inputs = tokenizer(prompt, return_tensors="pt") | |
| outputs = model.generate(**inputs, max_new_tokens=128) | |
| result = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| return result | |
| demo = gr.Interface( | |
| fn=classify_conspiracy, | |
| inputs=gr.Textbox( | |
| lines=5, | |
| placeholder="Enter text to classify...", | |
| label="Input Text" | |
| ), | |
| outputs=gr.Textbox( | |
| lines=10, | |
| label="Classification Result" | |
| ), | |
| title="ConspEmoLLM-v2 API", | |
| description="Classifies input text for conspiracy theories using the ConspEmoLLM-v2 LLM." | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |