Search Results for "lazarus-2.2.2-fpc-3.2.2-cross-i386-win32-win64.exe"
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Showing 27 open source projects for "lazarus-2.2.2-fpc-3.2.2-cross-i386-win32-win64.exe"
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Comet Backup - Fast, Secure Backup Software for MSPsComet is a flexible backup platform, giving you total control over your backup environment and storage destinations.
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Network Management Software and Tools for Businesses and Organizations | Auvik NetworksReduce IT headaches and save time with a proven solution for automated network discovery, documentation, and performance monitoring. Choose Auvik because you'll see value in minutes, and stay with us to improve your IT for years to come.
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LTX-2
Python inference and LoRA trainer package for the LTX-2 audio–video
LTX-2 is a powerful, open-source toolkit developed by Lightricks that provides a modular, high-performance base for building real-time graphics and visual effects applications. It is architected to give developers low-level control over rendering pipelines, GPU resource management, shader orchestration, and cross-platform abstractions so they can craft visually compelling experiences without starting from scratch. Beyond basic rendering scaffolding, LTX-2 includes optimized math libraries, resource loaders, utilities for texture and buffer handling, and integration points for native event loops and input systems. The framework targets both interactive graphical applications and media-rich experiences, making it a solid foundation for games, creative tools, or visualization systems that demand both performance and flexibility. ... -
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Hunyuan3D-2.1
From Images to High-Fidelity 3D Assets
...It supports both shape generation (mesh geometry) and texture generation modules. Physically Based Rendering texture synthesis to model realistic material effects, including reflections, subsurface scattering, etc. Cross-platform support (MacOS, Windows, Linux) via Python / PyTorch, including diffusers-style APIs. -
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PaddleOCR
Awesome multilingual OCR toolkits based on PaddlePaddle
PaddleOCR offers exceptional, multilingual, and practical Optical Character Recognition (OCR) tools that can help users train better models and apply them into practice. Inspired by PaddlePaddle, PaddleOCR is an ultra lightweight OCR system, with multilingual recognition, digit recognition, vertical text recognition, as well as long text recognition. It features a PPOCR series of high-quality pre-trained models, which includes: ultra lightweight ppocr_mobile series models, general... -
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CodeGeeX
CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)
CodeGeeX is a large-scale multilingual code generation model with 13 billion parameters, trained on 850B tokens across more than 20 programming languages. Developed with MindSpore and later made PyTorch-compatible, it is capable of multilingual code generation, cross-lingual code translation, code completion, summarization, and explanation. It has been benchmarked on HumanEval-X, a multilingual program synthesis benchmark introduced alongside the model, and achieves state-of-the-art performance compared to other open models like InCoder and CodeGen. CodeGeeX also powers IDE plugins for VS Code and JetBrains, offering features like code completion, translation, debugging, and annotation. ... -
Securden Privileged Account ManagerDiscover and manage administrator, service, and web app passwords, keys, and identities. Automate management with approval workflows. Centrally control, audit, monitor, and record all access to critical IT assets.
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DeepSeek VL2
Mixture-of-Experts Vision-Language Models for Advanced Multimodal
...While the internal architecture details are not fully documented publicly, the repo suggests that VL2 introduces enhancements over prior vision-language models (e.g. better scaling, cross-modal attention, more robust alignment) to improve grounding and multimodal understanding. -
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FireRedTTS-2
Long-form streaming TTS system for multi-speaker dialogue generation
...It features a specialized streaming speech tokenizer and a dual-transformer architecture that enables low latency and high-quality synthesis, making it suitable for interactive systems like chatbots, podcasts, and applications where dynamic turn-taking between speakers is essential. FireRedTTS2 supports multilingual output and speaker flexibility, enabling scenarios that involve language switching, cross-lingual voice cloning, and expressive dialogue generation that maintains consistency over longer utterances. -
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Kimi K2.5
Moonshot's most powerful AI model
Kimi K2.5 is Moonshot AI’s open-source, native multimodal agentic model built through continual pretraining on approximately 15 trillion mixed vision and text tokens. Based on a 1T-parameter Mixture-of-Experts (MoE) architecture with 32B activated parameters, it integrates advanced language reasoning with strong visual understanding. K2.5 supports both “Thinking” and “Instant” modes, enabling either deep step-by-step reasoning or low-latency responses depending on the task. Designed for... -
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DeepSeek Coder V2
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models
DeepSeek-Coder-V2 is the version-2 iteration of DeepSeek’s code generation models, refining the original DeepSeek-Coder line with improved architecture, training strategies, and benchmark performance. While the V1 models already targeted strong code understanding and generation, V2 appears to push further in both multilingual support and reasoning in code, likely via architectural enhancements or additional training objectives. The repository provides updated model weights, evaluation... -
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CogView4
CogView4, CogView3-Plus and CogView3(ECCV 2024)
...Compared to previous CogView versions, CogView4 introduces architectural upgrades, improved training pipelines, and larger-scale datasets, enabling stronger alignment between textual prompts and generated visual content. It emphasizes bilingual usability, making it well-suited for cross-lingual multimodal applications. The model also supports fine-tuning and downstream customization, extending its applicability to creative content generation, human–computer interaction, and research on vision-language alignment. -
Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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HeartMuLa
A Family of Open Sourced Music Foundation Models
HeartMuLa is the open-source library and reference implementation for the HeartMuLa family of music foundation models, designed to support both music generation and music-related understanding tasks in a cohesive stack. At the center is HeartMuLa, a music language model that generates music conditioned on inputs like lyrics and tags, with multilingual support that broadens the range of lyric-driven use cases. The project also includes HeartCodec, a music codec optimized for high... -
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CodeGeeX2
CodeGeeX2: A More Powerful Multilingual Code Generation Model
...Its backend powers the CodeGeeX IDE plugins for VS Code, JetBrains, and other editors, offering developers interactive AI assistance with features like infilling and cross-file completion. -
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LingBot-VLA
A Pragmatic VLA Foundation Model
LingBot-VLA is an open-source Vision-Language-Action (VLA) foundational AI model designed to serve as a general “brain” for real-world robotic manipulation by grounding multimodal perception and language into actionable motions. It has been pretrained on tens of thousands of hours of real robotic interaction data across multiple robot platforms, which enables it to generalize well to diverse morphologies and tasks without needing extensive retraining on each new bot. The model aims to bridge... -
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Qwen3-VL-Embedding
Multimodal embedding and reranking models built on Qwen3-VL
Qwen3-VL-Embedding (with its companion Qwen3-VL-Reranker) is a state-of-the-art multimodal embedding and reranking model suite built on the open-sourced Qwen3-VL foundation, developed to handle diverse inputs including text, images, screenshots, and videos. The core embedding model maps such inputs into semantically rich vectors in a unified representation space, enabling similarity search, clustering, and cross-modal retrieval. The reranking model then precisely scores relevance between a given query and candidate documents, enhancing retrieval accuracy in complex multimodal tasks. Together, they support advanced information retrieval workflows such as image-text search, visual question answering (VQA), and video-text matching, while providing out-of-the-box support for more than 30 languages. -
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Sapiens
High-resolution models for human tasks
...It integrates sensory inputs such as vision, audio, and proprioception into a unified learning architecture that allows agents to understand and adapt to their surroundings dynamically. The project emphasizes long-horizon reasoning and cross-modal grounding—connecting language, perception, and action into a single agentic model capable of following abstract goals. It includes simulation environments, datasets, and benchmarks for testing grounded understanding, imitation learning, and decision-making. The system’s modular pipeline supports both imitation-based and reinforcement-based training strategies, allowing flexible experimentation with different embodiments and tasks. -
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OpenAI Realtime Embedded
Instructions on how to use the Realtime API on Microcontrollers
...The repo includes pointers to an ESP32 implementation (maintained as esp32 branch) and documentation that Espressif offers an official example in openai_demo. It does not appear to include a full cross-platform embedded SDK in the main branch (the core content is mostly links and minimal README), but acts as a launching point for integrating realtime on microcontrollers. -
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Seamless Communication
Foundational Models for State-of-the-Art Speech and Text Translation
...The system architecture includes a real-time multimodal signal pipeline for audio, video, and sensor data, a dialog manager that can decide when to act (speak, gesture, point) or query, and a cross-modal reasoning layer that fuses perception with semantic context. The research prototype includes components for visual grounding (understanding when a user references something in view), gesture recognition and synthesis, and turn-taking mechanisms that mirror human conversational timing. Because latency and synchronization are critical, the codebase invests in asynchronous scheduling, overlap of perception and reasoning, and fast fallback responses. -
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HunyuanVideo-Avatar
Tencent Hunyuan Multimodal diffusion transformer (MM-DiT) model
HunyuanVideo-Avatar is a multimodal diffusion transformer (MM-DiT) model by Tencent Hunyuan for animating static avatar images into dynamic, emotion-controllable, and multi-character dialogue videos, conditioned on audio. It addresses challenges of motion realism, identity consistency, and emotional alignment. Innovations include a character image injection module, an Audio Emotion Module for transferring emotion cues, and a Face-Aware Audio Adapter to isolate audio effects on faces,... -
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NVIDIA Isaac GR00T
NVIDIA Isaac GR00T N1.5 is the world's first open foundation model
NVIDIA Isaac‑GR00T N1.5 is an open-source foundation model engineered for generalized humanoid robot reasoning and manipulation skills. It accepts multimodal inputs—such as language and images—and uses a diffusion transformer architecture built upon vision-language encoders, enabling adaptive robot behaviors across diverse environments. It is designed to be customizable via post-training with real or synthetic data. The vision-language model remains frozen during both pretraining and... -
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StudioOllamaUI
StudioOllamaUI is a local, portable interface for Ollama
StudioOllamaUI: Portable .The easiest way to run local AI Do you want to use AI but don't know what Docker is? Does the terminal scare you? StudioOllamaUI is for you. Zero Installation: Works on a fresh Windows installation. No Python, no libraries, no drama. 100% Portable: Just like a portable browser. Unzip, run, and that's it. It doesn't clutter your registry or leave traces on your disk. AI for Everyone: No expensive GPU? No problem. Optimized to run smoothly on your CPU... -
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Proximus for Ryzen AI
Runtime extension of Proximus enabling Deployment on AMD Ryzen™ AI
...Originally designed for use with Windows 11 Pro, this runtime was further enhanced to work under Linux environments, allowing developers and researchers to fully utilize the AMD AI Engine across both platforms. This cross-platform support is a major innovation, enabling AI workload portability, integration into CI environments, and deployment into Linux-based research and production pipelines. -
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Style Aligned
Official code for Style Aligned Image Generation via Shared Attention
StyleAligned is a diffusion-model editing technique and codebase that preserves the visual “style” of an original image while applying new semantic edits driven by text. Instead of fully re-generating an image—and risking changes to lighting, texture, or rendering choices—the method aligns internal features across denoising steps so the target edit inherits the source style. This alignment acts like a constraint on the model’s evolution, steering composition, palette, and brushwork even as... -
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Prompt-to-Prompt
Latent Diffusion and Stable Diffusion Implementation
Prompt-to-Prompt is a research codebase that demonstrates how to edit images generated by diffusion models using only changes to the text prompt. Instead of retraining or heavy fine-tuning, it manipulates the model’s cross-attention maps so the structure of the original image is largely preserved while semantics shift according to the revised prompt. The method supports gentle edits (e.g., style, color, lighting) as well as stronger semantic substitutions, and it can localize edits to specific words or regions by selectively updating attention. Because edits are steerable via prompt wording and token weighting, creators can iterate quickly, exploring variations without losing composition. ... -
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LLaMA.go
llama.go is like llama.cpp in pure Golang
llama.go is like llama.cpp in pure Golang. The code of the project is based on the legendary ggml.cpp framework of Georgi Gerganov written in C++ with the same attitude to performance and elegance. Both models store FP32 weights, so you'll needs at least 32Gb of RAM (not VRAM or GPU RAM) for LLaMA-7B. Double to 64Gb for LLaMA-13B. -
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MUSE
A library for Multilingual Unsupervised or Supervised word Embeddings
...By mapping languages into a common vector space, MUSE makes it straightforward to build cross-lingual applications where resources are scarce for some languages. The training and evaluation pipeline is lightweight and fast, so experimenting with different languages or initialization strategies is easy. Beyond dictionary induction, the learned embeddings are often used as building blocks for downstream tasks like classification, retrieval, or machine translation. -
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Hunyuan-MT-7B
Tencent’s 36-language state-of-the-art translation model
...It forms part of the Hunyuan Translation Model family, alongside Hunyuan-MT-Chimera, which ensembles outputs for even higher accuracy. Trained with a comprehensive framework spanning pretraining, cross-lingual pretraining, supervised fine-tuning, enhancement, and ensemble refinement, the model achieves competitive results against systems of similar or larger scale. At WMT25, Hunyuan-MT secured first place in 30 of the 31 translation categories it entered, highlighting its reliability in real-world multilingual use. The model offers flexible deployment options with variants such as FP8 quantization and ensemble configurations. ...
