Model: keeeeenw/MicroLlava
Author: keeeeenw
Pipeline: visual-question-answering
Library: transformers
Tags: transformers, safetensors, tinyllava, text-generation, pytorch, vision-language, visual-question-answering, custom_code, en, base_model:google/siglip2-so400m-patch14-384, base_model:finetune:google/siglip2-so400m-patch14-384, license:apache-2.0, model-index, region:us
Base models (finetune): id: google/siglip2-so400m-patch14-384
Card metadata: language: en
library_name: transformers
tags: pytorch, safetensors, vision-language, visual-question-answering
pipeline_tag: visual-question-answering
license: apache-2.0
base_model: google/siglip2-so400m-patch14-384, keeeeenw/MicroLlama
model-index: name: MicroLLaVA (MicroLLaMA 300M + SigLIP2-so400m-patch4-384)
results: task: type: visual-question-answering
name: VQAv2
dataset: name: VQAv2
type: vqav2
metrics: name: Overall Accuracy
type: accuracy
value: 56.91
verified: no, name: Yes/No Accuracy
type: accuracy
value: 72.32
verified: no, name: Number Accuracy
type: accuracy
value: 43.89
verified: no, name: Other Accuracy
type: accuracy
value: 46.65
verified: no
source: name: Internal Evaluation on VQAv2 test-dev
url: https://visualqa.org/download.html
Likes: 5 | All-time downloads: 285
Created: 2025-08-10 07:29:11