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Llava v1.5 7b Xtuner Pretrain

llava-v1.5-7b-xtuner-pretrain is a LLaVA projector pretrained from Vicuna-7B-v1.5 and CLIP-ViT-Large-patch14-336 on LLaVA-Pretrain dataset by XTuner.

TipoOtherVersãoRevision d035ccfBnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
80,0 MB
Versão
vRevision d035ccf
Atualizado
19 de set. de 2026
Downloads
15
Fonte
Hugging Face

Trecho da fonte

llava-v1.5-7b-xtuner-pretrain is a LLaVA projector pretrained from Vicuna-7B-v1.5 and CLIP-ViT-Large-patch14-336 on LLaVA-Pretrain dataset by XTuner.

Fontes

1 fonte
Hugging FacePrimárioVersão d035ccf49367f0a24143baee833cd5e4b73ffcf7
huggingface.co/xtuner/llava-v1.5-7b-xtuner-pretrain/tree/d035ccf49367f0a24143baee833cd5e4b73ffcf7

Verificado 4 de set.

Artefatos de modelo

1 artefato

epoch_1.pth

pth · 80,0 MB · SHA-256 f0a53fea99a1…61d2 · Hugging Face

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Trechos de fonte

2 trechos

--- datasets: - liuhaotian/LLaVA-Pretrain pipeline_tag: visual-question-answering --- <div align="center"> <img src="https://github.com/InternLM/lmdeploy/assets/36994684/0cf8d00f-e86b-40ba-9b54-dc8f1bc6c8d8" width="600"/> [![Generic badge](https://img.shields.io/badge/GitHub-%20XTuner-black.svg)](https://github.com/InternLM/xtuner) </div> ## Model llava-v1.5-7b-xtuner-pretrain is a LLaVA projector pretrained from [Vicuna-7B-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) and [CLIP-ViT-Large-patch14-336](https://huggingface.co/openai/clip-vit-large-patch14-336) on [LLaVA-Pretrain](https://huggingface.co/datasets/liuhaotian/LLaVA-Pretrain) dataset by [XTuner](https://github.com/InternLM/xtuner). The fine-tuned LLaVA model can be found on [xtuner/llava-v1.5-7b-xtuner](https://huggingface.co/xtuner/llava-v1.5-7b-xtuner). ## Citation ```bibtex @misc{2023xtuner, title={XTuner: A Toolkit for Efficiently Fine-tuning LLM}, author={XTuner Contributors}, howpublished = {\url{https://github.com/InternLM/xtuner}}, year={2023} } ```

Source context: 15 downloads · 2 likes · Pipeline visual-question-answering · Library transformers · Repo xtuner/llava-v1.5-7b-xtuner-pretrain