Search Results for "python-kinterbasdb" - Page 6
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Showing 291 open source projects for "python-kinterbasdb"
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Pearl
A Production-ready Reinforcement Learning AI Agent Library
Pearl is a production-ready reinforcement learning and contextual bandit agent library built for real-world sequential decision making. It is organized around modular components—policy learners, replay buffers, exploration strategies, safety modules, and history summarizers—that snap together to form reliable agents with clear boundaries and strong defaults. The library implements classic and modern algorithms across two regimes: contextual bandits (e.g., LinUCB, LinTS, SquareCB, neural... -
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
DINOv2 is a self-supervised vision learning framework that produces strong, general-purpose image representations without using human labels. It builds on the DINO idea of student–teacher distillation and adapts it to modern Vision Transformer backbones with a carefully tuned recipe for data augmentation, optimization, and multi-crop training. The core promise is that a single pretrained backbone can transfer well to many downstream tasks—from linear probing on classification to retrieval,... -
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CogView4
CogView4, CogView3-Plus and CogView3(ECCV 2024)
CogView4 is the latest generation in the CogView series of vision-language foundation models, developed as a bilingual (Chinese and English) open-source system for high-quality image understanding and generation. Built on top of the GLM framework, it supports multimodal tasks including text-to-image synthesis, image captioning, and visual reasoning. Compared to previous CogView versions, CogView4 introduces architectural upgrades, improved training pipelines, and larger-scale datasets,... -
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DreamCraft3D
Official implementation of DreamCraft3D
DreamCraft3D is DeepSeek’s generative 3D modeling framework / model family that likely extends their earlier 3D efforts (e.g. Shap-E or Point-E style models) with more capability, control, or expression. The name suggests a “dream crafting” metaphor—users probably supply textual or image prompts and generate 3D assets (point clouds, meshes, scenes). The repository includes model code, inference scripts, sample prompts, and possibly dataset preparation pipelines. It may integrate rendering or... -
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ChatPaper
Use ChatGPT to summarize the arXiv papers
ChatPaper is an AI-assisted research toolkit designed to accelerate academic reading and writing workflows. It uses language models to summarize papers and help researchers screen literature more efficiently. The project also supports full-paper translation, writing improvement, peer-review analysis, and responses to reviewer comments. It can retrieve recent arXiv papers based on keywords and time ranges for topic-focused research. Related tools can generate literature reviews, suggest paper... -
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Claude Plugins Community
Community plugin marketplace for Claude Cowork and Claude Code
Claude Plugins — Community is a read-only marketplace repository for community-contributed plugins compatible with Claude Cowork and Claude Code. It acts as the public mirror of Anthropic’s reviewed community plugin catalog. The marketplace metadata is synchronized nightly from Anthropic’s internal review pipeline. Listed plugins have passed automated security scanning and approval before distribution. Claude Code users can add the repository as a marketplace and install individual community... -
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Fara-7B
An Efficient Agentic Model for Computer Use
Fara-7B is a Microsoft initiative aimed at bringing rigor, transparency, and structured evaluation to AI systems through automated and customizable assessment frameworks. It provides stakeholders with a way to benchmark and evaluate models across dimensions such as fairness, robustness, security, privacy, and ethical considerations. Rather than relying on ad-hoc or manual review processes, FARA enables organizations to profile AI behavior using standardized tests, metrics, and reporting... -
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Kimi-Audio
Audio foundation model excelling in audio understanding
Kimi-Audio is an ambitious open-source audio foundation model designed to unify a wide array of audio processing tasks — from speech recognition and audio understanding to generative conversation and sound event classification — within a single cohesive architecture. Instead of fragmenting work across specialized models, Kimi-Audio handles automatic speech recognition (ASR), audio question answering, automatic audio captioning, speech emotion recognition, and audio-to-text chat in one... -
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DeepSeek Coder
DeepSeek Coder: Let the Code Write Itself
DeepSeek-Coder is a series of code-specialized language models designed to generate, complete, and infill code (and mixed code + natural language) with high fluency in both English and Chinese. The models are trained from scratch on a massive corpus (~2 trillion tokens), of which about 87% is code and 13% is natural language. This dataset covers project-level code structure (not just line-by-line snippets), using a large context window (e.g. 16K) and a secondary fill-in-the-blank objective... -
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Qwen2.5-Math
A series of math-specific large language models of our Qwen2 series
Qwen2.5-Math is a series of mathematics-specialized large language models in the Qwen2 family, released by Alibaba’s QwenLM. It includes base models (1.5B / 7B / 72B parameters), instruction-tuned versions, and a reward model (RM) to improve alignment. Unlike its predecessor Qwen2-Math, Qwen2.5-Math supports both Chain-of-Thought (CoT) reasoning and Tool-Integrated Reasoning (TIR) for solving math problems, and works in both Chinese and English. It is optimized for solving mathematical... -
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rwkv.cpp
INT4/INT5/INT8 and FP16 inference on CPU for RWKV language model
Besides the usual FP32, it supports FP16, quantized INT4, INT5 and INT8 inference. This project is focused on CPU, but cuBLAS is also supported. RWKV is a novel large language model architecture, with the largest model in the family having 14B parameters. In contrast to Transformer with O(n^2) attention, RWKV requires only state from the previous step to calculate logits. This makes RWKV very CPU-friendly on large context lengths. -
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Qwen3-Omni
Qwen3-omni is a natively end-to-end, omni-modal LLM
Qwen3-Omni is a natively end-to-end multilingual omni-modal foundation model that processes text, images, audio, and video and delivers real-time streaming responses in text and natural speech. It uses a Thinker-Talker architecture with a Mixture-of-Experts (MoE) design, early text-first pretraining, and mixed multimodal training to support strong performance across all modalities without sacrificing text or image quality. The model supports 119 text languages, 19 speech input languages, and... -
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LingBot-Video
Scaling Mixture-of-Experts Video Pretraining for Embodied Intelligence
LingBot-Video is a large-scale mixture-of-experts video generation model focused on embodied intelligence. It is designed to connect video synthesis with physical-world understanding instead of generating only visually appealing clips. The project includes dense and MoE model variants for text-to-image, text-to-video, and text-image-to-video workflows. Its training combines large-scale web video data with more than 70,000 hours of embodied data. A multi-reward system emphasizes aesthetics,... -
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LingBot-World 2.0
Infinite Worlds with Versatile Interactions
LingBot-World v2, also called LingBot-World-Infinity, is a world-modeling project for long-horizon interactive video generation. It extends the original LingBot-World with a causal pretraining approach for maintaining quality over ongoing interaction. The project supports richer interactive elements such as attacks, archery, spell-casting, shooting, and text-driven scene events. A distilled real-time variant is designed for rapid response and 720p, 60 FPS interactive streams. It also... -
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Hy-MT2 is a family of fast-thinking multilingual translation models built for complex real-world translation scenarios. It includes 1.8B, 7B, and 30B-A3B model sizes, giving users options for lightweight deployment, stronger general performance, or MoE-based capacity. The models support translation across 33 languages and are designed to follow detailed translation instructions in multiple languages. They can handle tasks involving terminology, style, personalization, delimiters, structured...
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Moondream
Tiny vision language model
Moondream is a creative code project and visual experimentation repository that explores generative graphics, aesthetic patterns, and interactive art through code. The project typically showcases procedural visualizations, algorithmic designs, and artistic experiments that push the boundaries of what can be expressed with programming languages and rendering frameworks. While the exact nature can vary by commit or branch, Moondream’s work often blends geometry, color theory, and motion to... -
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Gemma in PyTorch
The official PyTorch implementation of Google's Gemma models
gemma_pytorch provides the official PyTorch reference for running and fine-tuning Google’s Gemma family of open models. It includes model definitions, configuration files, and loading utilities for multiple parameter scales, enabling quick evaluation and downstream adaptation. The repository demonstrates text generation pipelines, tokenizer setup, quantization paths, and adapters for low-rank or parameter-efficient fine-tuning. Example notebooks walk through instruction tuning and evaluation... -
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ARC-AGI-1 Task Generator
Generates original ARC-AGI-1-style tasks distribution-matched
ARC-AGI-1 Task Generator creates new ARC-style reasoning tasks whose distribution is designed to resemble the public ARC-AGI-1 evaluation set. It provides fresh problems that models are less likely to have encountered during training or previous evaluation. The project is intended to complement public benchmark scores by testing whether reasoning abilities transfer to newly generated examples. Generated tasks use the standard ARC train-and-test JSON structure. This makes the output... -
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img2obj
Codex plugin that turns attached object images into code-only
img2obj is a Codex plugin that reconstructs an object from a reference image as procedural Three.js code rather than extracting or downloading a mesh. It first checks whether the image is suitable, then creates an ObjectSculptSpec describing geometry, materials, hierarchy, pivots, sockets, and visual priorities. Reconstruction proceeds through blockout, form, look development, and interaction phases so details are added in a controlled order. The plugin supports hard-surface objects, organic... -
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JoyAI-VL-Interaction
An Open Real-time Video-Language Interaction System
JoyAI-VL-Interaction is an open real-time video-language interaction system built around an 8B-scale vision-first model. It is designed to watch a webcam or livestream continuously and decide whether to speak, stay silent, or delegate a harder task. Unlike turn-based assistants, it focuses on event-driven interaction where timing matters as much as answer quality. The repository releases the model, training recipe, time-aligned interaction data, and deployable system together. Its system... -
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MiMo Audio
Audio Language Models are Few-Shot Learners
MiMo Audio is an open-source audio language model project focused on few-shot learning across speech and audio tasks. It explores how large-scale next-token prediction can help audio models generalize from a few examples or simple instructions. The project includes MiMo-Audio-7B-Base and MiMo-Audio-7B-Instruct, along with a dedicated MiMo-Audio tokenizer. It supports audio understanding, speech intelligence, spoken dialogue, instruction-following audio generation, and text-to-speech-style... -
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MiniMind-O
A 0.1B Omni model trained from scratch
MiniMind-O is an educational open-source project for building a small end-to-end Omni model from scratch. It extends the MiniMind family by exploring a model that can handle text, audio, and image inputs while producing text and streaming speech outputs. The project is designed to make multimodal AI training more accessible by keeping the model size small enough for ordinary personal hardware. It includes both mini and full training data paths, allowing learners to run a complete workflow... -
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TADA
Open Source Speech Language Model
TADA is an open-source speech-language modeling framework designed to unify spoken audio and text representations within a single generative architecture. The system focuses on aligning speech and text streams using a dual-alignment mechanism that synchronizes the acoustic signal with its textual representation. By modeling both modalities together, the framework allows developers to build systems capable of generating, understanding, and transforming speech and language simultaneously. This... -
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FireRedASR
Open-source industrial-grade ASR models
FireRedASR is an industrial-grade family of open-source automatic speech recognition models designed to provide high-precision speech-to-text performance across languages including Mandarin, English, and various Chinese dialects, achieving new state-of-the-art benchmarks on public test sets. The project includes multiple model variants to meet different application needs, such as high-accuracy end-to-end interaction using an encoder-adapter-LLM framework and efficient real-time recognition... -
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fast-stable-diffusion
Fast-stable-diffusion + DreamBooth
fast-stable-diffusion is a community-curated GitHub repository that provides Colab notebooks and integration examples for running Stable Diffusion and associated UIs like AUTOMATIC1111, ComfyUI, and DreamBooth directly on Google Colab environments. Rather than being a standalone packaged application, this project offers ready-to-use interactive notebooks that install and launch full-feature Stable Diffusion web UIs inside Colab without requiring complex local setups or GPU installations....
