Handle device and dtype better
Browse files
Makefile
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@@ -10,7 +10,7 @@ clean:
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rm -rf .venv
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run:
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source .venv/bin/activate ; python
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black-check:
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source .venv/bin/activate ; black . --check --verbose --line-length 120
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rm -rf .venv
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run:
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source .venv/bin/activate ; python app.py
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black-check:
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source .venv/bin/activate ; black . --check --verbose --line-length 120
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app.py
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@@ -3,16 +3,36 @@ from transformers import pipeline
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import gradio as gr
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import json
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# Initialize model pipeline
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model_id = "dylanhogg/gnaf-structured-address-v0.1-75a1791-20250921-063650"
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pipe = pipeline(
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"text-generation",
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model=model_id,
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dtype=
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device_map=
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)
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def parse_address(user_address: str) -> tuple[str, str]:
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"""Parse address and return both raw response and JSON"""
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@@ -24,8 +44,8 @@ def parse_address(user_address: str) -> tuple[str, str]:
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outputs = pipe(
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messages,
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max_new_tokens=
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do_sample=
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)
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response = outputs[0]["generated_text"]
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@@ -48,7 +68,6 @@ def parse_address(user_address: str) -> tuple[str, str]:
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return formatted_json, last_content
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# Create Gradio interface
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with gr.Blocks(title="Address Parser") as demo:
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gr.Markdown("# 🏠 Structured Address Parser")
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gr.Markdown("This model converts text addresses into structured JSON format.")
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@@ -64,7 +83,6 @@ with gr.Blocks(title="Address Parser") as demo:
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json_output = gr.Textbox(label="Structured JSON", interactive=False, lines=10)
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raw_output = gr.Textbox(label="Raw Model Output", interactive=False, lines=5)
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# Examples
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gr.Examples(
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examples=[
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"48a Pirrama Rd Pyrmont NSW 2009",
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@@ -99,10 +117,10 @@ with gr.Blocks(title="Address Parser") as demo:
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inputs=input_text,
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)
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# Handle events
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submit_btn.click(fn=parse_address, inputs=input_text, outputs=[json_output, raw_output])
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input_text.submit(fn=parse_address, inputs=input_text, outputs=[json_output, raw_output])
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# Launch the app
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if __name__ == "__main__":
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demo.launch()
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import gradio as gr
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import json
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model_id = "dylanhogg/gnaf-structured-address-v0.1-75a1791-20250921-063650"
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max_new_tokens = 256
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do_sample = False
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if torch.cuda.is_available():
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device = "cuda"
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dtype = torch.bfloat16 if torch.cuda.is_bf16_supported() else torch.float16
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device_map = "auto"
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print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
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elif torch.backends.mps.is_available():
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device = "mps"
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dtype = torch.float16
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device_map = None
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else:
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device = "cpu"
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dtype = torch.float32
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device_map = None
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print(f"Device settings: {device=}, {dtype=}, {device_map=}")
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pipe = pipeline(
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"text-generation",
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model=model_id,
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dtype=dtype,
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device_map=device_map,
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)
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print(f"Model {pipe.model=}")
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print(f"Model config {pipe.model.config=}")
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def parse_address(user_address: str) -> tuple[str, str]:
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"""Parse address and return both raw response and JSON"""
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outputs = pipe(
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messages,
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max_new_tokens=max_new_tokens,
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do_sample=do_sample,
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)
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response = outputs[0]["generated_text"]
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return formatted_json, last_content
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with gr.Blocks(title="Address Parser") as demo:
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gr.Markdown("# 🏠 Structured Address Parser")
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gr.Markdown("This model converts text addresses into structured JSON format.")
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json_output = gr.Textbox(label="Structured JSON", interactive=False, lines=10)
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raw_output = gr.Textbox(label="Raw Model Output", interactive=False, lines=5)
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gr.Examples(
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examples=[
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"48a Pirrama Rd Pyrmont NSW 2009",
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inputs=input_text,
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)
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submit_btn.click(fn=parse_address, inputs=input_text, outputs=[json_output, raw_output])
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input_text.submit(fn=parse_address, inputs=input_text, outputs=[json_output, raw_output])
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if __name__ == "__main__":
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print("Launching app...")
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demo.launch()
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print("Done.")
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