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This model is an int4 model with group_size 128 and symmetric quantization of Qwen/Qwen3-VL-30B-A3B-Instruct generated by intel/auto-round. Please refer to Section Generate the model for more details. Please follow the license of the original model. The model can produce factually incorrect output, and should not be relied on to produce factually accurate information. Because of the limitations of the pretrained model and the finetuning datasets, it is possible that this model could generate lewd, biased or otherwise offensive outputs. Therefore, before deploying any applications of the model, developers should perform safety testing.
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View details ↗The original source of this model is : runwayml/stable-diffusion-v1-5. This model is just optimized and converted to Intermediate Representation (IR) using OpenVino's Model Optimizer and POT tool to run on Intel's Hardware - CPU, GPU, NPU. We have FP16 and INT8 versions of the model. Please note currently only unet model is quantized to int8. Intended to be used with: - GIMP plugin openvino-ai-plugins-gimp - Blender Addon dream-textures-openvino
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗tiny-random-falcon
Intel基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗tiny-random-gpt2
IntelThis is useful for functional testing (not quality generation, since its weights are random) on optimum-intel
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View details ↗tiny-random-llama2
Intel基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗tvp-base
IntelThe TVP model was proposed in Text-Visual Prompting for Efficient 2D Temporal Video Grounding by Yimeng Zhang, Xin Chen, Jinghan Jia, Sijia Liu, Ke Ding. The goal of this model is to incorporate trainable prompts into both visual inputs and textual features to temporal video grounding(TVG) problems. It was introduced in this paper. Relevant factors: The model's performance may vary across different video content, such as variations in video quality, lighting conditions, or genres (e.g., action vs. dialogue-heavy scenes). Evaluation factors: Performance has been evaluated on benchmark datasets like Charades-STA and ActivityNet Captions, focusing on metrics relevant to temporal video grounding accuracy. Model performance measures: The model employs metrics such as the Temporal-Distance IoU (TDIoU) loss for efficient learning and performance evaluation in TVG tasks.
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View details ↗zoedepth-nyu
IntelZoeDepth model fine-tuned on the NYU dataset. It was introduced in the paper ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth by Shariq et al. and first released in this repository. ZoeDepth extends the DPT framework for metric (also called absolute) depth estimation, obtaining state-of-the-art results. Disclaimer: The team releasing ZoeDepth did not write a model card for this model so this model card has been written by the Hugging Face team.
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View details ↗zoedepth-nyu-kitti
IntelZoeDepth model fine-tuned on the NYU and KITTI datasets. It was introduced in the paper ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth by Shariq et al. and first released in this repository. ZoeDepth extends the DPT framework for metric (also called absolute) depth estimation, obtaining state-of-the-art results. Disclaimer: The team releasing ZoeDepth did not write a model card for this model so this model card has been written by the Hugging Face team.
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View details ↗CAT-Q
IntelLabsChina基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗intellifold
intelligenAI基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗II-Medical-8B
Intelligent-Internet基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗II-Medical-8B-1706
Intelligent-Internet基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗II-Medical-8B-1706-GGUF
Intelligent-Internet基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗II-Search-4B
Intelligent-Internet基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗DEIMv2_DINOv3_L_COCO
Intellindust基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗DEIMv2_DINOv3_M_COCO
Intellindust基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗DEIMv2_DINOv3_S_COCO
Intellindust基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗DEIMv2_DINOv3_X_COCO
Intellindust基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗DEIMv2_HGNetv2_N_COCO
IntellindustThis model has been pushed to the Hub using the PytorchModelHubMixin integration: - Code: [More Information Needed] - Paper: [More Information Needed] - Docs: [More Information Needed]
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View details ↗imagine-v10
Interchained基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗imagine-v12
Interchained基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗imagine-v9
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