• Go From AI Idea to AI App Fast Icon
    Go From AI Idea to AI App Fast

    One platform to build, fine-tune, and deploy ML models. No MLOps team required.

    Access Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
    Try Free
  • Try Google Cloud Risk-Free With $300 in Credit Icon
    Try Google Cloud Risk-Free With $300 in Credit

    No hidden charges. No surprise bills. Cancel anytime.

    Use your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
    Start Free
  • 1
    GLM-4.6

    GLM-4.6

    Agentic, Reasoning, and Coding (ARC) foundation models

    GLM-4.6 is the latest iteration of Zhipu AI’s foundation model, delivering significant advancements over GLM-4.5. It introduces an extended 200K token context window, enabling more sophisticated long-context reasoning and agentic workflows. The model achieves superior coding performance, excelling in benchmarks and practical coding assistants such as Claude Code, Cline, Roo Code, and Kilo Code. Its reasoning capabilities have been strengthened, including improved tool usage during inference...
    Downloads: 105 This Week
    Last Update:
    See Project
  • 2
    ChatGLM3

    ChatGLM3

    ChatGLM3 series: Open Bilingual Chat LLMs | Open Source Bilingual Chat

    ...The family includes base and long-context variants (8K/32K/128K). The repo ships Python APIs, CLI and web demos (Gradio/Streamlit), an OpenAI-format API server, and a compact fine-tuning kit. Quantization (4/8-bit), CPU/MPS support, and accelerator backends (TensorRT-LLM, OpenVINO, chatglm.cpp) enable lightweight local or edge deployment.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 3
    CogVLM

    CogVLM

    A state-of-the-art open visual language model

    CogVLM is an open-source visual–language model suite—and its GUI-oriented sibling CogAgent—aimed at image understanding, grounding, and multi-turn dialogue, with optional agent actions on real UI screenshots. The flagship CogVLM-17B combines ~10B visual parameters with ~7B language parameters and supports 490×490 inputs; CogAgent-18B extends this to 1120×1120 and adds plan/next-action outputs plus grounded operation coordinates for GUI tasks. The repo provides multiple ways to run models...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 4
    Curated Transformers

    Curated Transformers

    PyTorch library of curated Transformer models and their components

    ...Supports state-of-the-art transformer models, including LLMs such as Falcon, Llama, and Dolly v2. Implementing a feature or bugfix benefits all models. For example, all models support 4/8-bit inference through the bitsandbytes library and each model can use the PyTorch meta device to avoid unnecessary allocations and initialization.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Streamline Azure Security with Palo Alto Networks VM-Series Icon
    Streamline Azure Security with Palo Alto Networks VM-Series

    Centrally manage physical and virtualized firewalls with Panorama

    Improve your security posture and reduce incident response time. Use the VM-Series to natively analyze Azure traffic and dynamically drive policy updates based on workload changes.
    Learn more
  • 5
    LLaVA

    LLaVA

    Visual Instruction Tuning: Large Language-and-Vision Assistant

    Visual instruction tuning towards large language and vision models with GPT-4 level capabilities.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 6
    llama2-webui

    llama2-webui

    Run any Llama 2 locally with gradio UI on GPU or CPU from anywhere

    Running Llama 2 with gradio web UI on GPU or CPU from anywhere (Linux/Windows/Mac).
    Downloads: 0 This Week
    Last Update:
    See Project
  • 7
    GLM-130B

    GLM-130B

    GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)

    ...Trained on over 400 billion tokens (200B English, 200B Chinese), it achieves performance surpassing GPT-3 175B, OPT-175B, and BLOOM-176B on multiple benchmarks, while also showing significant improvements on Chinese datasets compared to other large models. The model supports efficient inference via INT8 and INT4 quantization, reducing hardware requirements from 8× A100 GPUs to as little as a single server with 4× RTX 3090s. Built on the SwissArmyTransformer (SAT) framework and compatible with DeepSpeed and FasterTransformer, it supports high-speed inference (up to 2.5× faster) and reproducible evaluation across 30+ benchmark tasks.
    Downloads: 1 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB