Microsoft

{
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}

{
  "id": "microsoft/phi-3-vision-128k-instruct",
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}

{
  "id": "microsoft/phi-3.5-moe-instruct",
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}

{
  "name": "TRELLIS",
  "publisher": "microsoft",
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    "Run-on-RTX",
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  "id": "microsoft/trellis",
  "description": "MSFT TRELLIS is a 3D AI model that generates high-quality 3D assets from text or image inputs.",
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}

{
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  "name": "Microsoft: Phi 4",
  "created": 1736489872,
  "description": "[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. At 14 billion...",
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    "tokenizer": "Other",
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  "knowledge_cutoff": "2024-06-30",
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/microsoft/phi-4/endpoints"
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}

{
  "id": "@cf/microsoft/resnet-50",
  "source": 1,
  "name": "@cf/microsoft/resnet-50",
  "description": "50 layers deep image classification CNN trained on more than 1M images from ImageNet",
  "task": {
    "id": "00cd182b-bf30-4fc4-8481-84a3ab349657",
    "name": "Image Classification",
    "description": "Image classification models take an image input and assigns it labels or classes."
  },
  "created_at": "2023-09-25 19:21:11.898",
  "tags": [],
  "properties": [
    {
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      ]
    },
    {
      "property_id": "info",
      "value": "https://www.microsoft.com/en-us/research/blog/microsoft-vision-model-resnet-50-combines-web-scale-data-and-multi-task-learning-to-achieve-state-of-the-art/"
    }
  ],
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}