Create app.py

app.py

@@ -0,0 +1,19 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModel
+import torch
+
+model_name = "Qwen/Qwen-Embedding-0.6B"
+tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+model = AutoModel.from_pretrained(model_name, trust_remote_code=True)
+
+def get_embedding(text):
+    inputs = tokenizer(text, return_tensors="pt")
+    with torch.no_grad():
+        embeddings = model(**inputs).last_hidden_state.mean(dim=1).squeeze().tolist()
+    return embeddings
+
+demo = gr.Interface(fn=get_embedding,
+                    inputs=gr.Textbox(lines=2, placeholder="Enter text..."),
+                    outputs="json",
+                    title="Qwen Embedding Generator")
+demo.launch()