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import gradio as gr
import torch
from PIL import Image
from unsloth import FastVisionModel
from peft import PeftModel
# -----------------------------------------------------------------------------
# 1. Load Model Correctly (No Double Patching)
# -----------------------------------------------------------------------------
# Load model with 4-bit quantization
model, tokenizer = FastVisionModel.from_pretrained(
"unsloth/Llama-3.2-11B-Vision-Instruct",
load_in_4bit = True,
device_map = "auto",
)
# -----------------------------------------------------------------------------
# 2. Load Your Fine-Tuned Adapter CORRECTLY
# -----------------------------------------------------------------------------
# Loading adapter WITHOUT get_peft_model()
model = PeftModel.from_pretrained(model, "fine_tuned_model")
model = model.merge_and_unload() # Merge adapters into base model
model.to("cuda")
model.eval()
# -----------------------------------------------------------------------------
# 3. Data preprocessing step
# -----------------------------------------------------------------------------
def analyze(image, user_prompt):
if image.mode != "RGB":
image = image.convert("RGB")
messages = [
{"role": "user", "content": [
{"type": "image", "image": image},
{"type": "text", "text": user_prompt}
]}
]
input_text = tokenizer.apply_chat_template(messages, add_generation_prompt=True)
inputs = tokenizer(
image,
input_text,
return_tensors = "pt",
add_special_tokens = False,
).to("cuda")
with torch.no_grad():
outputs = model.generate(
**inputs,
max_new_tokens = 512,
use_cache = True,
temperature = 1.0,
min_p = 0.1,
)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
# -----------------------------------------------------------------------------
# 4. Launch Interface
# -----------------------------------------------------------------------------
gr.Interface(
fn=analyze,
inputs=[
gr.Image(type="pil", label="Upload Medical Scan"),
gr.Textbox(
placeholder="Example: 'Describe any abnormalities in this chest X-ray'",
label="Your Question",
lines=2
)
],
outputs=gr.Textbox(label="Expert Analysis"),
title=" DAS medhub Radiology AI Assistant (Fine-Tuned)",
description="Upload a medical image and ask questions about it"
).launch(server_port=7860, debug=False) |