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Awesome GitHub RepositoriesAutoregressive Transformers

Transformer architectures that generate sequences by predicting tokens based on previous outputs.

Distinguishing note: Focuses on the specific two-stage generation architecture for audio.

Explore 12 awesome GitHub repositories matching artificial intelligence & ml · Autoregressive Transformers. Refine with filters or upvote what's useful.

Awesome Autoregressive Transformers GitHub Repositories

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  • microsoft/vibevoiceالصورة الرمزية لـ microsoft

    microsoft/VibeVoice

    49,394عرض على GitHub↗

    VibeVoice is a generative artificial intelligence platform designed for text-to-speech synthesis. It functions as a neural audio generation framework that converts written text into natural-sounding spoken audio, specifically engineered to maintain consistent vocal characteristics and narrative prosody across extended passages of content. The system distinguishes itself through its ability to generate long-form conversational speech while preserving speaker identity and linguistic content. By utilizing latent space disentanglement, the model separates speaker traits from the input text, allow

    Utilizes autoregressive transformer architectures to predict sequential audio tokens for consistent long-form speech generation.

    Python
    عرض على GitHub↗49,394
  • 2noise/chatttsالصورة الرمزية لـ 2noise

    2noise/ChatTTS

    39,464عرض على GitHub↗

    ChatTTS is a conversational text-to-speech generative model designed to convert written dialogue into natural sounding audio. It functions as a multilingual speech synthesis framework capable of producing human-like audio across different languages and speaker profiles. The system is distinguished by its ability to generate interactive dialogue with realistic vocal nuances. It utilizes a speech nuance controller to insert specific tokens that trigger non-verbal elements, such as laughter, pauses, and interjections, during the synthesis process. The project includes a streaming audio generato

    Implements an autoregressive transformer architecture to predict audio tokens for sequential speech generation.

    Pythonagentchatchatgpt
    عرض على GitHub↗39,464
  • fishaudio/fish-speechالصورة الرمزية لـ fishaudio

    fishaudio/fish-speech

    24,928عرض على GitHub↗

    This project is a generative speech synthesis engine that converts text into high-fidelity human speech. It utilizes a two-stage autoregressive transformer architecture that separates semantic token prediction from acoustic detail reconstruction to balance linguistic accuracy with audio quality. The system is designed to support multilingual output and conversational AI development, enabling the generation of context-aware speech that maintains flow across multiple dialogue turns. The platform distinguishes itself through a production-ready inference server that employs continuous batching to

    Separates semantic prediction from acoustic reconstruction to balance linguistic accuracy and audio fidelity.

    Pythonllamatransformertts
    عرض على GitHub↗24,928
  • neonbjb/tortoise-ttsالصورة الرمزية لـ neonbjb

    neonbjb/tortoise-tts

    14,864عرض على GitHub↗

    Tortoise-tts is a neural text-to-speech engine and voice cloning toolkit designed for high-quality audio generation. It functions as a zero-shot synthesis system, meaning it can generate speech for unseen speakers without requiring additional training or fine-tuning for each new voice. The system specializes in replicating human vocal characteristics using small sets of reference audio clips. It allows for the extraction of voice latents to mimic specific speakers, the generation of random synthetic identities, and the blending of multiple voice profiles to create hybrid vocal identities. Th

    Uses autoregressive transformer architectures to maintain natural prosody and speech rhythms during audio token prediction.

    Jupyter Notebook
    عرض على GitHub↗14,864
  • borisdayma/dalle-miniالصورة الرمزية لـ borisdayma

    borisdayma/dalle-mini

    14,756عرض على GitHub↗

    dalle-mini is a text-to-image model and generative AI system designed to transform natural language descriptions into synthetic images. It functions as an image generation training toolkit and a generative model capable of creating visual representations from text prompts. The project provides a containerized deployment for consistent execution across different computing environments. It includes the necessary scripts and configuration files to train custom generative models from datasets. The system utilizes an autoregressive transformer architecture that treats visual data as discrete toke

    Implements an autoregressive transformer architecture to generate image tokens sequentially from text descriptions.

    Python
    عرض على GitHub↗14,756
  • sparkaudio/spark-ttsالصورة الرمزية لـ SparkAudio

    SparkAudio/Spark-TTS

    10,930عرض على GitHub↗

    Spark-TTS is a deep learning text-to-speech synthesis engine designed to convert written text into high-fidelity audio. It utilizes a transformer-based architecture and autoregressive sequence modeling to generate coherent speech, transforming linguistic input into natural-sounding waveforms through neural speech codec synthesis. The platform distinguishes itself through zero-shot voice cloning, which allows users to mimic a target speaker’s unique vocal identity using only a short reference audio sample without requiring additional model training. It also features cross-lingual phonetic mapp

    Implements an autoregressive transformer architecture to generate high-fidelity speech by predicting audio tokens based on preceding context.

    Python
    عرض على GitHub↗10,930
  • nvidia/cosmosالصورة الرمزية لـ NVIDIA

    NVIDIA/cosmos

    10,494عرض على GitHub↗

    Cosmos is an open platform of world models, datasets, and tools for building physical AI systems such as robots and autonomous vehicles. It provides video generation and video understanding models that can generate synthetic videos and world simulations from text, image, video, or action inputs, and analyze videos to produce captions, event timestamps, spatial bounding boxes, and next-action predictions. The platform includes a world simulation generator that produces images, videos, synchronized audio, and action-conditioned rollouts for synthetic data, alongside a visual content analyzer th

    Processes video tokens autoregressively to output structured text predictions like captions, bounding boxes, and next actions.

    Jupyter Notebook
    عرض على GitHub↗10,494
  • nlpxucan/wizardlmالصورة الرمزية لـ nlpxucan

    nlpxucan/WizardLM

    9,486عرض على GitHub↗

    WizardLM is a large language model and instruction-tuning framework designed to execute sophisticated coding, mathematical, and conversational tasks. It functions as an AI system for mathematical reasoning and code generation, as well as a synthetic dataset generator used to train other language models. The project is distinguished by its evolutionary instruction tuning, which uses a method to rewrite simple instructions into complex tasks. This process expands training dataset difficulty and produces a high volume of open-domain tasks across various difficulty levels. The system covers capa

    Utilizes a transformer-based autoregressive architecture to predict subsequent tokens and maintain conversational context.

    Python
    عرض على GitHub↗9,486
  • google/traxالصورة الرمزية لـ google

    google/trax

    8,304عرض على GitHub↗

    Trax is a deep learning framework and hardware-agnostic tensor engine designed for designing and training neural networks. It serves as a research tool providing high-level combinators for composing complex architectures, alongside a dedicated library for building transformer models and a toolkit for reinforcement learning. The framework is distinguished by its support for reversible and sparse transformer architectures, which reduce memory and computational overhead. It enables a single set of model instructions to execute across different hardware backends without changing the underlying co

    Provides a mechanism for sequential output generation by looping previous predictions back into the model.

    Python
    عرض على GitHub↗8,304
  • eleutherai/gpt-neoالصورة الرمزية لـ EleutherAI

    EleutherAI/gpt-neo

    8,275عرض على GitHub↗

    GPT-Neo is an open-source distributed training framework designed for scaling GPT-2 and GPT-3-style language models across multiple devices using mesh-tensorflow for model parallelism. It provides the infrastructure to train transformer-based language models with billions of parameters across distributed computing environments, making large-scale language model research accessible outside of proprietary systems. The framework supports training both autoregressive GPT-style models and masked language models like BERT or RoBERTa, with configurable masking strategies and token handling. It inclu

    Ships an autoregressive transformer decoder that generates text token-by-token with causal attention masking.

    Pythongptgpt-2gpt-3
    عرض على GitHub↗8,275
  • zyphra/zonosالصورة الرمزية لـ Zyphra

    Zyphra/Zonos

    7,225عرض على GitHub↗

    Zonos is a controllable audio synthesis engine and large language model for text-to-speech. It serves as a multilingual speech generator capable of producing audio in English, Japanese, Chinese, French, and German. The system provides zero-shot voice cloning, allowing the replication of specific human voices using short audio samples. It supports the capture of nuanced behaviors, such as whispering, and provides parametric control over speaking rate, pitch, frequency, and emotional tone. The project covers a broad range of expressive speech synthesis and custom audio generation capabilities,

    Implements an autoregressive transformer architecture to predict speech tokens from text and acoustic embeddings.

    Python
    عرض على GitHub↗7,225
  • multimodal-art-projection/yueالصورة الرمزية لـ multimodal-art-projection

    multimodal-art-projection/YuE

    6,292عرض على GitHub↗

    YuE: Open Full-song Music Generation Foundation Model, something similar to Suno.ai but open

    Generates music tokens sequentially using a transformer decoder with causal masking and shared latent conditioning.

    Pythonaiaudio-generationdeep-learning
    عرض على GitHub↗6,292
  1. Home
  2. Artificial Intelligence & ML
  3. Autoregressive Transformers

استكشف الوسوم الفرعية

  • Sampling MechanismsTechniques for generating sequential outputs by feeding previous predictions back into the model. **Distinct from Autoregressive Transformers:** Focuses on the sampling process itself rather than the overall transformer architecture
  • Video Token ReasonersProcesses video tokens autoregressively to output structured text predictions like captions, bounding boxes, and next actions. **Distinct from Autoregressive Transformers:** Distinct from Autoregressive Transformers: specifically applies autoregressive decoding to video tokens for structured text output, not general sequence generation.