3 مستودعات
Flow-matching architectures specifically designed to generate text via continuous embeddings.
Distinct from Flow-Matching Frameworks: Specializes flow-matching for text-token generation rather than the common image-based application.
Explore 3 awesome GitHub repositories matching artificial intelligence & ml · Continuous Text Generation. Refine with filters or upvote what's useful.
This project is a machine learning research automation system designed to manage the full research lifecycle, from idea discovery to final paper submission. It utilizes markdown-based skill templates to execute autonomous research tasks and manage iterative loops of deep review and experimentation. The system distinguishes itself through integrated capabilities for academic communication and integrity auditing. It can automate the generation of LaTeX papers, conference slide decks, and evidence-grounded peer review rebuttals. To ensure rigor, it employs cross-model review routing and adversar
Transforms noise into clean embeddings using flow matching for continuous text generation.
AI NovelGenerator هي أداة لتوليد الخيال الطويل باستخدام نماذج لغوية كبيرة. تعمل كمهندس سردي ومساعد كتابة، حيث تؤتمت إنشاء الروايات متعددة الفصول مع إدارة هيكل القصة العام وتتبع الشخصيات. يتميز المشروع بنظام استرجاع سياق دلالي ومدقق اتساق قصة يعمل بالذكاء الاصطناعي. تستخدم هذه الأدوات البحث الدلالي لاسترجاع تفاصيل قصة محددة من فصول سابقة ومسح النص المولد بحثاً عن تناقضات في الحبكة أو عدم اتساق سلوكي. يغطي النظام دورة حياة سردية كاملة، بما في ذلك تصميم أساس القصة، وبناء العالم، وتخطيط هيكل الرواية. يستخدم خط أنابيب متعدد المراحل لصياغة فصول متماسكة ويدمج ورشة عمل لسير العمل الإبداعي لإدارة الإعدادات والتدقيق اللغوي.
Provides automated scanning of generated text to identify logical plot contradictions and character inconsistencies.
ExecuTorch is a lightweight C++ runtime for deploying PyTorch models on mobile, embedded, and edge hardware. It provides an ahead-of-time compilation pipeline that exports, quantizes, and lowers model graphs into compact serialized programs, then executes them through a minimal runtime with hardware acceleration and on-device large language model inference capabilities. The project distinguishes itself through a hardware accelerator delegate system that partitions model subgraphs and offloads computation to specialized backends including NPUs, GPUs, and DSPs from Apple, Arm, Intel, MediaTek,
ExecuTorch continues text generation from a specific point in the cache, enabling stateful continuation.