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{
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"bomFormat": "CycloneDX",
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"serialNumber": "urn:uuid:3055ead6-57c6-4f53-b237-31c297a9a0db",
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"version": 1,
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"metadata": {
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"timestamp": "2025-06-05T09:41:54.385491+00:00",
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"component": {
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"type": "machine-learning-model",
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"bom-ref": "ByteDance-Seed/UI-TARS-7B-SFT-2563bff1-2155-555e-9ebd-c56f1c3410c5",
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"name": "ByteDance-Seed/UI-TARS-7B-SFT",
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"externalReferences": [
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{
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"url": "https://huggingface.co/ByteDance-Seed/UI-TARS-7B-SFT",
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"type": "documentation"
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}
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],
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"modelCard": {
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"modelParameters": {
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"task": "image-text-to-text",
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"architectureFamily": "qwen2_vl",
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"modelArchitecture": "Qwen2VLForConditionalGeneration"
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},
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"properties": [
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{
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"name": "library_name",
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"value": "transformers"
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},
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"authors": [
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{
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"name": "ByteDance-Seed"
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}
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],
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"licenses": [
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{
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"license": {
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"id": "Apache-2.0",
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"url": "https://spdx.org/licenses/Apache-2.0.html"
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}
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}
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],
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"description": "UI-TARS is a next-generation native GUI agent model designed to interact seamlessly with graphical user interfaces (GUIs) using human-like perception, reasoning, and action capabilities. Unlike traditional modular frameworks, UI-TARS integrates all key components\u2014perception, reasoning, grounding, and memory\u2014within a single vision-language model (VLM), enabling end-to-end task automation without predefined workflows or manual rules.<!--  --><p align=\"center\"><img src=\"https://github.com/bytedance/UI-TARS/blob/main/figures/UI-TARS-vs-Previous-SOTA.png?raw=true\" width=\"90%\"/><p><p align=\"center\"><img src=\"https://github.com/bytedance/UI-TARS/blob/main/figures/UI-TARS.png?raw=true\" width=\"90%\"/><p><!--  -->This repository contains the model for the paper [UI-TARS: Pioneering Automated GUI Interaction with Native Agents](https://huggingface.co/papers/2501.12326).Code: https://github.com/bytedance/UI-TARS",
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"tags": [
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"transformers",
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"safetensors",
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"qwen2_vl",
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"image-text-to-text",
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"multimodal",
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"gui",
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"conversational",
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"en",
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"arxiv:2501.12326",
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"license:apache-2.0",
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"text-generation-inference",
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"endpoints_compatible",
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"region:us"
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]
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}
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}
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} |