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Basic Visual Language Model

For the Chinese version of the README, please refer to 中文文档.

ArtOtherVersionRevision a6334e8CBewertung

Modellquelle

Art
Other
Dateigröße
41,0–728 MB
Version
vRevision a6334e8
Aktualisiert
16. Okt. 2026
Downloads
0
Quelle
Hugging Face

Quellenbeschreibung

Building Your Own Multimodal Large Model from Scratch

For the Chinese version of the README, please refer to 中文文档.

Model Architecture 🤖

In the VLM (Visual Language Model), the visual component utilizes the CLIP or SIGLIP models, which have already achieved preliminary semantic alignment. A two-layer MLP is used for feature mapping. By overriding the forward method of the QWenModel, the corresponding image tokens are replaced with visual features.

GitHub Repository 🏠

The code for running the model can be found at Basic-Visual-Language-Model.

References 📚

Special thanks to the following projects for their great work 🙌:

Contact ✉

If you have any questions or ideas, feel free to reach out to me 😊:

[email protected]

I will respond as soon as I see your email!

Quellen

1 Quelle
Hugging FacePrimärVersion a6334e8c4386bfe2287dda4759bd37b219e1e6ca
huggingface.co/xinyanghuang/Basic-Visual-Language-Model/tree/a6334e8c4386bfe2287dda4759bd37b219e1e6ca

Verifiziert 28. Aug.

Modellartefakte

4 Artefakte

checkpoint-19000/checkpoint-19000/adapter_model.bin

bin · 728 MB · SHA-256 d0b0d273c5dc…8ee2 · Hugging Face

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checkpoint-19000/checkpoint-19000/other_params.bin

bin · 41,0 MB · SHA-256 7db2025e8322…d821 · Hugging Face

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checkpoint-36000/checkpoint-36000/adapter_model.bin

bin · 728 MB · SHA-256 bab67b05b624…335c · Hugging Face

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checkpoint-36000/checkpoint-36000/other_params.bin

bin · 41,0 MB · SHA-256 620d634331b2…3cea · Hugging Face

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Quellenauszüge

2 Auszüge

--- license: apache-2.0 pipeline_tag: visual-question-answering --- # Building Your Own Multimodal Large Model from Scratch For the Chinese version of the README, please refer to [中文文档](README_zh.md). ## Model Architecture 🤖 In the VLM (Visual Language Model), the visual component utilizes the `CLIP` or `SIGLIP` models, which have already achieved preliminary semantic alignment. A two-layer MLP is used for feature mapping. By overriding the `forward` method of the `QWenModel`, the corresponding `image` tokens are replaced with visual features. ## GitHub Repository 🏠 The code for running the model can be found at [Basic-Visual-Language-Model](https://github.com/xinyanghuang7/Basic-Visual-Language-Model/tree/main). ## References 📚 Special thanks to the following projects for their great work 🙌: - https://github.com/WatchTower-Liu/VLM-learning/tree/main - https://github.com/QwenLM/Qwen - https://github.com/haotian-liu/LLaVA ## Contact ✉ If you have any questions or ideas, feel free to reach out to me 😊: [email protected] I will respond as soon as I see your email!

Source context: 0 downloads · 1 likes · Pipeline visual-question-answering · Repo xinyanghuang/Basic-Visual-Language-Model