Update app.py: better error handling, show_error=True
Browse files
app.py
CHANGED
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@@ -6,24 +6,40 @@ Provides a web UI to trigger LoRA fine-tuning of OLMo 2 1B Instruct
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on tokenized video data, then push the trained model to EeshaAI/zeeb.
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"""
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import gradio as gr
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from train_on_hf_spaces import train
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def run_training():
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"""Run the training pipeline
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with gr.Blocks(
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title="Zeeb β Video-LLM Trainer",
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theme=gr.themes.Soft(),
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css="""
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#logbox { font-family: 'Courier New', monospace; font-size: 13px; line-height: 1.5; }
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#title { text-align: center; }
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.contain { max-width: 800px; margin: auto; }
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"""
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) as demo:
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gr.Markdown(
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@@ -31,18 +47,15 @@ with gr.Blocks(
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# π¬ Zeeb β Video-LLM Trainer
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Fine-tune **OLMo 2 1B Instruct** with **LoRA (r=4)** to generate video tokens.
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Trained model is automatically pushed to [EeshaAI/zeeb](https://huggingface.co/EeshaAI/zeeb).
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"""
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elem_id="title",
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)
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train_btn = gr.Button("π Start Training", variant="primary", size="lg")
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logbox = gr.Textbox(
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label="Training Log",
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max_lines=100,
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interactive=False,
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show_copy_button=True,
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)
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@@ -65,4 +78,4 @@ with gr.Blocks(
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if __name__ == "__main__":
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demo.launch(server_name="0.0.0.0", server_port=7860)
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on tokenized video data, then push the trained model to EeshaAI/zeeb.
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"""
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import os
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import sys
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import io
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import gradio as gr
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def run_training():
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"""Run the training pipeline, capturing all output."""
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# Capture all prints and logs
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old_stdout = sys.stdout
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old_stderr = sys.stderr
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sys.stdout = buffer = io.StringIO()
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sys.stderr = buffer
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log_output = ""
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try:
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from train_on_hf_spaces import train
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for log_msg in train("tokenized_dataset.json"):
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log_output += log_msg
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except Exception as e:
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import traceback
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log_output += f"\nβ ERROR: {e}\n"
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log_output += traceback.format_exc()
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finally:
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sys.stdout = old_stdout
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sys.stderr = old_stderr
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return log_output
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with gr.Blocks(
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title="Zeeb β Video-LLM Trainer",
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theme=gr.themes.Soft(),
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) as demo:
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gr.Markdown(
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# π¬ Zeeb β Video-LLM Trainer
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Fine-tune **OLMo 2 1B Instruct** with **LoRA (r=4)** to generate video tokens.
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Trained model is automatically pushed to [EeshaAI/zeeb](https://huggingface.co/EeshaAI/zeeb).
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"""
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)
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train_btn = gr.Button("π Start Training", variant="primary", size="lg")
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logbox = gr.Textbox(
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label="Training Log",
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lines=30,
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max_lines=200,
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interactive=False,
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show_copy_button=True,
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)
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if __name__ == "__main__":
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demo.launch(server_name="0.0.0.0", server_port=7860, show_error=True)
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