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Update app.py
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app.py
CHANGED
@@ -17,20 +17,22 @@ bnb_config = BitsAndBytesConfig(
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bnb_4bit_compute_dtype=torch.float16
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)
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# Load model
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model = AutoModel.from_pretrained(
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"ContactDoctor/Bio-Medical-MultiModal-Llama-3-8B-V1",
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quantization_config=bnb_config,
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device_map="auto",
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torch_dtype=torch.float16,
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trust_remote_code=True,
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token=api_token
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)
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tokenizer = AutoTokenizer.from_pretrained(
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"ContactDoctor/Bio-Medical-MultiModal-Llama-3-8B-V1",
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trust_remote_code=True,
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token=api_token
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)
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def analyze_input(image_data, question):
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@@ -73,19 +75,18 @@ def analyze_input(image_data, question):
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demo = gr.Interface(
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fn=analyze_input,
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inputs=[
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gr.Image(type="numpy", label="Medical Image"),
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gr.Textbox(label="Question", placeholder="Enter your medical query...")
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],
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outputs=gr.JSON(label="Analysis"),
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title="Bio-Medical MultiModal Analysis",
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description="Ask questions with or without an image",
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)
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# Launch with
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demo.launch(
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share=True,
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server_name="0.0.0.0",
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server_port=7860
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enable_queue=True
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)
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bnb_4bit_compute_dtype=torch.float16
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)
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# Load model with revision pinning
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model = AutoModel.from_pretrained(
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"ContactDoctor/Bio-Medical-MultiModal-Llama-3-8B-V1",
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quantization_config=bnb_config,
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device_map="auto",
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torch_dtype=torch.float16,
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trust_remote_code=True,
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token=api_token,
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revision="main" # Pin to specific revision
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)
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tokenizer = AutoTokenizer.from_pretrained(
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"ContactDoctor/Bio-Medical-MultiModal-Llama-3-8B-V1",
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trust_remote_code=True,
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token=api_token,
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revision="main" # Pin to specific revision
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)
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def analyze_input(image_data, question):
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demo = gr.Interface(
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fn=analyze_input,
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inputs=[
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gr.Image(type="numpy", label="Medical Image"),
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gr.Textbox(label="Question", placeholder="Enter your medical query...")
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],
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outputs=gr.JSON(label="Analysis"),
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title="Bio-Medical MultiModal Analysis",
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description="Ask questions with or without an image",
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flagging_mode="never" # Updated from allow_flagging
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)
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# Launch with simplified parameters
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demo.launch(
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share=True,
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server_name="0.0.0.0",
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server_port=7860
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)
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