use different dicts for v1-v2 emotion9 predictions
0a077e0
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emotion9 v2 label dicts
32d95f0
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use v2 emotion9 models if available
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removed table schema
410b6ef
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bigquery model list (write)
7e0dad9
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removed html slop
8869f68
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cap_media_demo -> cap_media
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cap media should follow the naming template
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pep8
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cache twitter minor model
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use twitter model for social media
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updated model selection logic
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use gradio 4 theme
08a8f54
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use the latest gradio
c56cb4d
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gradio downgrade
8353d5b
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removed spaces before gradio downgrade
6d86fd5
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set torch threads
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use max length of 64 with padding
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safer approach to clean cache
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maybe like this?
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typo
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set max length to 64
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use padding
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delete every blob not just .bin files
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delete unused model weights FIXED
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delete unused model weights (before JIT)
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time profiling for prediction
7cbaea3
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hf cleanup as context
3f77878
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hf http cache cleanup
b1b87fb
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show disk usage for /data as well (du)
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debug df -h before scanning cache
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add v1
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verified
media2
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media2
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media2
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Create cap_media2.py
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manifesto fix
a55b33f
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config jit issue
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jit pt2
0a394ee
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JIT tracing
fb1a253
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debug logits
0b09517
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lazy jit for dev
5ed0b8d
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jit tracing fix
654bf8b
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torch!
ca62943
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parameters removed
3abd99d
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jit test...
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JIT...
caa0374
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updated gradio
afcc557
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utils.py
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preload models
d68fe8b
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