Create app.py

app.py

@@ -0,0 +1,44 @@
+from PIL import Image
+from unsloth import FastVisionModel
+model, tokenizer = FastVisionModel.from_pretrained(
+    model_name = "davidr99/qwen2-7b-instruct-blackjack", # YOUR MODEL YOU USED FOR TRAINING
+    load_in_4bit = True, # Set to False for 16bit LoRA
+)
+FastVisionModel.for_inference(model) # Enable for inference!
+
+import gradio as gr
+
+def blackjack_ai(image):
+    image = Image.fromarray(image.astype('uint8'), 'RGB')
+    instruction = "Write the LaTeX representation for this image."
+    
+    messages = [
+        {"role": "user", "content": [
+            {"type": "image"},
+            {"type": "text", "text": instruction}
+        ]}
+    ]
+    input_text = tokenizer.apply_chat_template(messages, add_generation_prompt = True)
+    inputs = tokenizer(
+        image,
+        input_text,
+        add_special_tokens = False,
+        return_tensors = "pt",
+    ).to("cuda")
+    
+    from transformers import TextStreamer
+    text_streamer = TextStreamer(tokenizer, skip_prompt = True)
+    _ = model.generate(**inputs, streamer = text_streamer, max_new_tokens = 128,
+                       use_cache = True, temperature = 1.5, min_p = 0.1)
+
+    return text_streamer
+
+with gr.Blocks() as demo:
+   
+    image = gr.Image()
+    submit = gr.Button("Submit")
+    output = gr.TextArea()
+
+    submit.click(blackjack_ai, inputs=[image], outputs=[output])
+    
+demo.launch()