[DOCS] Rel branch refs#710
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| This article explains how to prepare models based on the [Hugging Face](https://huggingface.co/welcome) [`transformers`](https://github.com/huggingface/transformers) library for integration with the Deep Learning Streamer pipeline. | ||
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| Many transformer-based models can be converted to OpenVINO™ IR format using [optimum-cli](https://huggingface.co/docs/optimum-intel/en/openvino/export). DL Streamer supports selected Hugging Face architectures for tasks such as image classification, object detection, audio transcription, and more. See the [Supported Models](https://docs.openedgeplatform.intel.com/dev/edge-ai-libraries/dlstreamer/supported_models.html) table for details. | ||
| Many transformer-based models can be converted to OpenVINO™ IR format using [optimum-cli](https://huggingface.co/docs/optimum-intel/en/openvino/export). DL Streamer supports selected Hugging Face architectures for tasks such as image classification, object detection, audio transcription, and more. See the [Supported Models](https://docs.openedgeplatform.intel.com/2026.0/edge-ai-libraries/dlstreamer/supported_models.html) table for details. |
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Please consider changing the name of the file 👆
lvms.md → transformers.md
This article also covers RT-DETR / RT-DETRv2 object detection, Whisper speech recognition, and Phi4MM VLMs, which are not all “large vision models” in the narrow sense.
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Fair enough, you make a good point here; however, I'd rather address this in a separate PR (for instance here: #702, or a new one altogether), if that's okay.
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Yeah sure, separate PR sounds good
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Years look solid, links work. Pls check one comment @wiwaszko-intel
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LGTM, please address merge conflict
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