Create app.py

app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+from transformers import pipeline, BitsAndBytesConfig
+import torch
+
+quantization_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_compute_dtype=torch.float16
+)
+model_id = "llava-hf/llava-1.5-7b-hf"
+
+pipe = pipeline("image-to-text",
+                model=model_id)
+
+
+def launch(image, prompt):
+    prompt = f"USER: <image>\n{prompt}\nASSISTANT:"
+    outputs = pipe(image, prompt=prompt, generate_kwargs={"max_new_tokens": 200})
+    return out[0]['generated_text']
+
+iface = gr.Interface(launch,
+                     inputs=[gr.Image(type='pil'), 'text'],
+                     outputs="text")
+
+iface.launch()