Qwen2.5 VL 7B Instruct
Qwen2.5-VL-7B-Instruct-GGUF is a repository on Hugging Face that supplies GGUF quantized files of the Qwen2.5-VL 7B vision-language model. It is intended for local inference of a multimodal model capable of processing both images and video alongside text. The repository is provided by unsloth.
The files include variants such as Qwen2.5-VL-7B-Instruct-BF16.gguf and Qwen2.5-VL-7B-Instruct-IQ4_NL.gguf. A chat template is defined that handles messages containing text, image, or video content by inserting specific vision and image or video pad tokens. The template supports counting multiple images or videos in a conversation and adds optional identifiers such as "Picture 1:" or "Video 1:" before the visual tokens. It uses special tokens including vision_start, vision_end, image_pad, video_pad, im_start, and im_end.
The total file size across the GGUF files is 15237851776 bytes. These quantized models are distributed for use with compatible inference engines that accept the GGUF format. The repository forms part of the broader collection of foundation models available on the platform.
No pricing, licensing terms, or additional deployment details beyond the GGUF files and chat template are stated.
Overview
4 featuresQwen2.5 VL 7B Instruct sits in PulseGate's Multimodal & vision category. It focuses on running a capable 7B vision-language model efficiently on consumer hardware using quantized GGUF format. Qwen2.5 VL 7B Instruct is an open-source project aimed at Local AI users and developers. The project is open source (Apache-2.0). It runs on the web, the command line, and API.
It is developed by Unsloth, and it first shipped in 2024. Development happens publicly on GitHub with 19.6k stars. The category is crowded — PulseGate's index counts 25 comparable projects. Key capabilities include Vision Language, GGUF Quantization, and Local Inference.
Summary written by a language model from the project’s public pages.
- Vision Language
- GGUF Quantization
- Local Inference
- Image and Video Input
Built with & integrations
- AWS
- x-amz-cf-id header · x-amz-cf-pop header · via header
- openai
- bgpt- in the HTML
- local_oss
- bollama in the HTML · bllama in the HTML · bvllm in the HTML
Trust & compliance
Indexing history
1What PulseGate has recorded for this listing
- Indexed21 Jul · 17:09 UTCunsloth/Qwen2.5-VL-7B-Instruct-GGUF verified against its public sourceSource: PulseGate · Open
Frequently asked questions about Qwen2.5 VL 7B Instruct
- What is Qwen2.5 VL 7B Instruct?
- Qwen2.5 VL 7B Instruct focuses on running a capable 7B vision-language model efficiently on consumer hardware using quantized GGUF format. It is catalogued under Multimodal & vision on PulseGate.
- Who is Qwen2.5 VL 7B Instruct for?
- Qwen2.5 VL 7B Instruct is an open-source project built for Local AI users and developers.
- Is Qwen2.5 VL 7B Instruct free?
- Yes — Qwen2.5 VL 7B Instruct is open source under the Apache-2.0 license and free to use.
- What platforms does Qwen2.5 VL 7B Instruct run on?
- Qwen2.5 VL 7B Instruct runs on the web, the command line, and API.
- Is Qwen2.5 VL 7B Instruct still maintained?
- Unverified. Qwen2.5 VL 7B Instruct has not been re-checked since it entered the index, so there is no finding either way — and only a positive finding would say otherwise.
- What are alternatives to Qwen2.5 VL 7B Instruct?
- Similar projects tracked by PulseGate include Qwen2.5 VL 3B Instruct, Qwen3 VL 2B Instruct, and Qwen2.5 VL 7B Instruct.Qwen2.5 VL 3B InstructQwen3 VL 2B InstructQwen2.5 VL 7B Instruct
- Who makes Qwen2.5 VL 7B Instruct?
- Qwen2.5 VL 7B Instruct is developed by Unsloth.
- When did Qwen2.5 VL 7B Instruct launch?
- Qwen2.5 VL 7B Instruct first shipped in 2024.
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