Showing 4 open source projects for "6.2"

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    VisualGLM-6B

    VisualGLM-6B

    Chinese and English multimodal conversational language model

    VisualGLM-6B is an open-source multimodal conversational language model developed by ZhipuAI that supports both images and text in Chinese and English. It builds on the ChatGLM-6B backbone, with 6.2 billion language parameters, and incorporates a BLIP2-Qformer visual module to connect vision and language. In total, the model has 7.8 billion parameters. Trained on a large bilingual dataset — including 30 million high-quality Chinese image-text pairs from CogView and 300 million English pairs — VisualGLM-6B is designed for image understanding, description, and question answering. ...
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  • 2
    ChatGLM-6B

    ChatGLM-6B

    ChatGLM-6B: An Open Bilingual Dialogue Language Model

    ChatGLM-6B is an open bilingual (Chinese + English) conversational language model based on the GLM architecture, with approximately 6.2 billion parameters. The project provides inference code, demos (command line, web, API), quantization support for lower memory deployment, and tools for finetuning (e.g., via P-Tuning v2). It is optimized for dialogue and question answering with a balance between performance and deployability in consumer hardware settings. Support for quantized inference (INT4, INT8) to reduce GPU memory requirements. ...
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  • 3

    slurm-roll

    Slurm Resource Manager for Rocks Clusters

    Slurm is a replacement for other resource management software and schedulers like gridengine or torque. The slurm roll integrates very well into a rocks clusters installation. In the folder addons, there are a lot of useful rolls for rocks clusters 6.1 and 6.2. These rolls do not depend on slurm. Please see Discussion for further information and support
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    Downloads: 1 This Week
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  • 4

    miRStat

    identification of common sets of microRNAs for groups of genes

    miRStat enables identification of regulatory microRNA targeting several genes in a custom gene group. This Python application is based on the TargetScan 6.2 microRNA target prediction data. Conserved and Nonconserved site context+ scores files are required (unzip and place to directory with program). Available at http://targetscan.org/cgi-bin/targetscan/data_download.cgi?db=vert_61
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