11 projects for "most" with 2 filters applied:

  • Our Free Plans just got better! | Auth0 Icon
    Our Free Plans just got better! | Auth0

    With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

    You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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  • Enterprise-grade ITSM, for every business Icon
    Enterprise-grade ITSM, for every business

    Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity.

    Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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  • 1
    LTX-2.3

    LTX-2.3

    Official Python inference and LoRA trainer package

    LTX-2.3 is an open-source multimodal artificial intelligence foundation model developed by Lightricks for generating synchronized video and audio from prompts or other inputs. Unlike most earlier video generation systems that only produced silent clips, LTX-2 combines video and audio generation in a unified architecture capable of producing coherent audiovisual scenes. The model uses a diffusion-transformer-based architecture designed to generate high-fidelity visual frames while simultaneously producing corresponding audio elements such as speech, music, ambient sound, or effects. ...
    Downloads: 138 This Week
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  • 2
    MiniMind-O

    MiniMind-O

    A 0.1B Omni model trained from scratch

    ...It includes both mini and full training data paths, allowing learners to run a complete workflow quickly or reproduce the released model setup more closely. The implementation emphasizes native PyTorch code instead of relying on high-level third-party abstractions. minimind-o is most useful for developers and researchers who want to understand how multimodal and speech-capable AI systems are built from the ground up.
    Downloads: 3 This Week
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  • 3
    VOID

    VOID

    Video Object and Interaction Deletion

    ...Built on top of transformer-based architectures and fine-tuned for video inpainting tasks, the system uses interaction-aware mask conditioning to ensure temporal consistency across frames. One of its most notable capabilities is its ability to simulate realistic scene behavior after object removal, such as causing an object to fall naturally if its support is removed, which significantly enhances realism.
    Downloads: 2 This Week
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  • 4
    CLIP

    CLIP

    CLIP, Predict the most relevant text snippet given an image

    CLIP (Contrastive Language-Image Pretraining) is a neural model that links images and text in a shared embedding space, allowing zero-shot image classification, similarity search, and multimodal alignment. It was trained on large sets of (image, caption) pairs using a contrastive objective: images and their matching text are pulled together in embedding space, while mismatches are pushed apart. Once trained, you can give it any text labels and ask it to pick which label best matches a given...
    Downloads: 0 This Week
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  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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  • 5
    Step3-VL-10B

    Step3-VL-10B

    Multimodal model achieving SOTA performance

    ...Despite having only about 10 billion parameters, it delivers performance that rivals or even surpasses much larger models (10×–20× larger) on a wide range of multimodal benchmarks covering reasoning, perception, and complex tasks, positioning it as one of the most powerful models in its class. It achieves this efficiency and strong performance through unified pre-training on a massive 1.2 trillion-token multimodal corpus that jointly optimizes a language-aligned perception encoder with a powerful decoder, creating deep synergy between image processing and text understanding.
    Downloads: 0 This Week
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  • 6
    DeiT (Data-efficient Image Transformers)
    ...Training involves carefully tuned augmentations, regularization, and optimization schedules to stabilize learning and improve sample efficiency. The repo offers pretrained checkpoints, reference scripts, and ablation studies that clarify which ingredients matter most for data-efficient ViT training.
    Downloads: 0 This Week
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  • 7
    Kimi K2.6

    Kimi K2.6

    Multimodal agent model for coding, orchestration, and autonomy

    ...Beyond coding, it can transform prompts and visual inputs into production-ready interfaces and lightweight full-stack outputs with structured layouts, interactivity, and polished visual detail. One of its most distinctive capabilities is horizontal agent scaling, supporting up to 300 sub-agents and 4,000 coordinated steps in a single run, which enables parallel task decomposition and end-to-end completion of outputs such as documents, websites, and spreadsheets. Architecturally, it uses a 1T-parameter Mixture-of-Experts design with 32B activated parameters, a MoonViT vision encoder, and a 256K context window.
    Downloads: 0 This Week
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  • 8
    Command A+

    Command A+

    4-bit Command A+ model for enterprise agents and multilingual tasks

    ...The W4A4 release applies 4-bit weight and activation quantization mainly to MoE experts, preserving attention components at full precision to reduce quality loss while improving speed, latency, and hardware efficiency. Cohere recommends W4A4 for most users because it offers a smaller hardware footprint with negligible benchmark differences compared to BF16 and FP8 versions. The model supports a 128K input context and 64K output length, covers 48 languages, and includes conversational tool-use capabilities with JSON-schema tools and optional citation grounding.
    Downloads: 0 This Week
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  • 9
    MiMo-V2.5-Pro

    MiMo-V2.5-Pro

    Flagship MoE model for long-context agents and complex coding

    MiMo-V2.5-Pro is Xiaomi’s flagship Mixture-of-Experts (MoE) model built for the most demanding agentic, software engineering, and long-horizon reasoning tasks. It features approximately 1.02 trillion total parameters with 42B activated per inference, balancing extreme capability with efficient execution. The model supports a 1 million token context window, enabling it to maintain coherence across long workflows involving thousands of tool calls and multi-step reasoning chains. ...
    Downloads: 0 This Week
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  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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  • 10
    DeepSeek-V4-Pro

    DeepSeek-V4-Pro

    Flagship MoE model for advanced reasoning, coding, and agents

    ...Architecturally, it introduces optimizations to reduce compute and memory costs while improving stability across long sequences. DeepSeek-V4-Pro is positioned as the high-end variant of the V4 family, outperforming most open-source models in areas such as agentic coding, STEM reasoning, and world knowledge, and approaching the performance of leading closed-source systems. It also supports advanced reasoning modes and tool-based workflows, enabling autonomous task execution.
    Downloads: 0 This Week
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  • 11
    Mistral Large 3 675B Base 2512

    Mistral Large 3 675B Base 2512

    Frontier-scale 675B multimodal base model for custom AI training

    Mistral Large 3 675B Base 2512 is the foundational, pre-trained version of the Mistral Large 3 family, built as a frontier-scale multimodal Mixture-of-Experts model with 41B active parameters and a total size of 675B. It is trained from scratch using 3000 H200 GPUs, making it one of the most advanced and compute-intensive open-weight models available. As the base version, it is not fine-tuned for instruction following or reasoning, making it ideal for teams planning their own domain-specific finetuning or custom training pipelines. The model is engineered for reliability, long-context comprehension, and stable performance across many enterprise, scientific, and knowledge-intensive workloads. ...
    Downloads: 0 This Week
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