Voice generation is amazing, but what about giving orders to your character using your voice? It's possible using Automatic Speech Recognition (ASR) models like Whisper. Interested? We wrote a tutorial on how to use ASR with Unity
MACHINE LEARNING
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List of Open Language Models for Commercial Use
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GitHub – eugeneyan/open-llms: A list of open LLMs available for commercial use. https://bit.ly/3MG7VRA #AI #MachineLearning #DeepLearning #LLMs #DataScience
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LoRA Implementation Added to Lit-Parrot Project
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Just added LoRA the other day (PR still in progress: https://
github.com/Lightning-AI/l
it-parrot/pull/128#pullrequestreview-1477273133
…) and will do some comparisons soon! -
Share Model Weights on Hugging Face Hub
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Congratulations on such a fantastic feat! Would be really cool to host the weights on the hugging face hub! Happy to help!
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Five Amazing Ways Meta Uses Generative AI Technology
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5 Amazing Ways Meta (Facebook) Is Using Generative AI
#AI #AIio #BigData #ML #NLU #Futureofwork @TunstallAsc @StrategyFintech @TamaraMcCleary @TerenceLeungSF @psb_dc @thomaspower @vinod1975 @ylecun http://
ow.ly/RUN730svHSY -
LLaMA-Adapter: Efficient LLM Fine-tuning with Tunable Prefixes
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I really like the LLaMA-Adapter method! In a nutshell, it's about finetuning LLMs more efficiently. In a nutshell, it's adding a tunable prefix to the key and value tensors in the self-attention layers. Fun fact: it's not specific to LLaMA. Use it with any LLM!
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IoU Loss Functions for Object Detection: GIoU, DIoU, CIoU
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🚀Blog-tastic Tuesdays🚀
— Satya Mallick (@LearnOpenCV) 13 juin 2023
Dive into the world of object detection with #DeepLearning!https://t.co/egztROZxfW
Check out our latest read as we break down the IoU Loss Functions (GIoU, DIoU, CIoU)#AI #MachineLearning pic.twitter.com/AcwvIf33QwBlog-tastic Tuesdays Dive into the world of object detection with #DeepLearning! https://
learnopencv.com/iou-loss-funct
ions-object-detection/
… Check out our latest read as we break down the IoU Loss Functions (GIoU, DIoU, CIoU) #AI #MachineLearning -
Generative Adversarial Neural Networks in Deep Learning
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#DeepLearning Generative Adversarial Neural Networks #AILabPage #VinsLens @KirkDBorne @SwissCognitive @alvinfoo @mclynd @SpirosMargaris @ipfconline1 @Fabriziobustama @FrRonconi @enricomolinari @ingliguori @schmarzo @asokan_telecom @SBUCloud @terence_mills
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FNet performance limitations compared to attention-based architectures
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Yeah, for some applications it may be sufficient. But FNet doesn't outperform a contemporary attention-based architecture though
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Model Explainability in Machine Learning Systems
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Does your model work? Can it explain itself? @HeatherGorr talks about explainability and #MachineLearning http://
spr.ly/6019Oah4N @ElectronicDesgn