Test model

app.py

@@ -1,7 +1,43 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import os
+
+hf_token = os.environ.get("HF_TOKEN")
+
+model = AutoModelForCausalLM.from_pretrained(
+    "Qwen/CodeQwen1.5-7B-Chat",
+    torch_dtype="auto",
+    device_map="auto",
+    token=hf_token
+)
+tokenizer = AutoTokenizer.from_pretrained("Qwen/CodeQwen1.5-7B-Chat", token=hf_token)
+
+messages = [
+    {"role": "system", "content": "You are a helpful assistant."},
+]
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+def greet(prompt):
+    messages.append({"role": "user", "content": prompt})
+    text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+    )
+    model_inputs = tokenizer([text], return_tensors="pt")
+
+    generated_ids = model.generate(
+        model_inputs.input_ids,
+        max_new_tokens=512
+    )
+    generated_ids = [
+        output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+    ]
+
+    response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0].text
+    
+    messages.append({"role": "bot", "content": response})
+
+    return response
 
 demo = gr.Interface(fn=greet, inputs="text", outputs="text")
 demo.launch()

requirements.txt

@@ -0,0 +1,2 @@
+transformers
+torch