sherlockchou86/VideoPipe
Cross-platform video structuring (video analysis) framework, please give a star if you find it helpful:).
Language:C++
Total stars: 400
Stars trend:
#cplusplus
#ai, #behaviouranalysis, #cv, #deeplearning, #deepstream, #facerecognition, #featureextraction, #gstreamer, #imageclassification, #imageenhancement, #imagesegmentation, #licenseplaterecognition, #objectdetection, #opencv, #reid, #similaritysearch, #videoanalysis, #videoprocessing
Cross-platform video structuring (video analysis) framework, please give a star if you find it helpful:).
Language:C++
Total stars: 400
Stars trend:
17 Apr 2024
5pm ▏ +1
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7pm +0
8pm +0
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18 Apr 2024
12am ██▌ +20
1am ████▎ +34
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3am █▍ +11#cplusplus
#ai, #behaviouranalysis, #cv, #deeplearning, #deepstream, #facerecognition, #featureextraction, #gstreamer, #imageclassification, #imageenhancement, #imagesegmentation, #licenseplaterecognition, #objectdetection, #opencv, #reid, #similaritysearch, #videoanalysis, #videoprocessing
PaulPauls/llama3_interpretability_sae
A complete end-to-end pipeline for LLM interpretability with sparse autoencoders (SAEs) using Llama 3.2, written in pure PyTorch and fully reproducible.
Language:Python
Total stars: 364
Stars trend:
#python
#featureextraction, #featuresteering, #llama3, #llminterpretability, #openresearch, #pytorch, #sparseautoencoder
A complete end-to-end pipeline for LLM interpretability with sparse autoencoders (SAEs) using Llama 3.2, written in pure PyTorch and fully reproducible.
Language:Python
Total stars: 364
Stars trend:
22 Nov 2024
12am ██▊ +22
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11am █▎ +10#python
#featureextraction, #featuresteering, #llama3, #llminterpretability, #openresearch, #pytorch, #sparseautoencoder