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Flet enables developers to easily build realtime web, mobile and desktop apps in Python. No frontend experience required.
From anything to mesh like human artists. Official impl. of "MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenization"
Source files for plugin documentation (https://3studioonline.github.io/TSBC-Documentation)
PyTorch implementation for the APoT quantization (ICLR 2020)
PowerShell automation to rebuild llama.cpp for a Windows environment.
Sniff out which async library your code is running under
Stable Diffusion web UI
High-speed Large Language Model Serving for Local Deployment
AppAgent: Multimodal Agents as Smartphone Users, an LLM-based multimodal agent framework designed to operate smartphone apps.
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
Get up and running with Llama 3.3, DeepSeek-R1, Phi-4, Gemma 2, and other large language models.
Awesome-LLM: a curated list of Large Language Model
BIDARA is a GPT-4 chatbot that was instructed to help scientists and engineers understand, learn from, and emulate the strategies used by living things to create sustainable designs and technologie…
A simple, high-quality voice conversion tool focused on ease of use and performance.
Tacotron 2 - PyTorch implementation with faster-than-realtime inference
This is a list of sound, audio and music development tools which contains machine learning, audio generation, audio signal processing, sound synthesis, spatial audio, music information retrieval, m…
End-to-End PyTorch-based neural speech synthesis toolkit
A program to dub non-english media with modern AI speech synthesis, diarization, and voice cloning!
Fully automated video maker using motion graphics and text-to-speech synthesis to turn newsletters into daily YouTube videos.
Natural Language Processing Pipeline - Sentence Splitting, Tokenization, Lemmatization, Part-of-speech Tagging and Dependency Parsing
PyTorch Implementation of Non-autoregressive Expressive (emotional, conversational) TTS based on FastSpeech2, supporting English, Korean, and your own languages.
PyTorch Implementation of Google's Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions. This implementation supports both single-, multi-speaker TTS and several techniques …
GAN-based Mel-Spectrogram Inversion Network for Text-to-Speech Synthesis
Text-to-Speech Gradio webui using RVC and edge-tts
Try out deep learning models online on Google Colab
A python package to analyze and compare voices with deep learning