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TinyLLaVA Qwen2.5 0.5B Instruct Dinov2 Small

Pretrain stage only, 4630 epochs

Fontehuggingface.co/sbrzz/TinyLLaVA-Qwen2.5-0.5B-Instruct-dinov2-small/tree/3843430d96f08bbfe5eb34c4321d57b8ef5a8412
TipoText modelModelo baseQwen/Qwen2.5-0.5B-InstructVersãoFP16Cnota

Fonte do modelo

Tipo
Text model
Tamanho do arquivo
987 MB
Modelo base
Qwen/Qwen2.5-0.5B-Instruct
Versão
vFP16
Atualizado
30 de out. de 2026
Downloads
14
Fonte
Hugging Face

Descrição da fonte

Pretrain stage only, 4630 epochs

Introduction

We use the powerful TinyLLaVA Factory to create a super small image-text-to-text model.

The goal is to make it possible to run LLaVA models on edge devices (with few gigabytes of memory).

For LLM and vision tower, we choose OpenELM-270M-Instruct and facebook/dinov2-small, respectively.

POPE:

Category# SamplesTPFPTNFNAccuracyPrecisionRecallF1 ScoreYes Ratio
Adversarial3000131212502501880.5210.5120.8750.6460.854
Popular3000131212362641880.5250.5150.8750.6480.849
Random2910131211852251880.5280.5250.8750.6560.858

TEXTVQA

Samples 5000, Accuracy 0% (:-|)

SCIENCEQA

Samples 4241, Correct: -, Accuracy: -%, IMG-Accuracy: -%

MMMU

Category# SamplesAccuracy
Overall9000.280
Overall-Art and Design1200.208
Art300.167
Art Theory300.200
Design300.367
Music300.100
Overall-Business1500.213
Accounting300.100
Economics300.367
Finance300.200
Management300.233
Marketing300.167
Overall-Science1500.300
Biology300.300
Chemistry300.133
Geography300.300
Math300.333
Physics300.433
Overall-Health and Medicine1500.340
Basic Medical Science300.300
Clinical Medicine300.133
Diagnostics and Laboratory Med.300.333
Pharmacy300.400
Public Health300.533
Overall-Humanities and Soc. Sci.1200.342
History300.300
Literature300.567
Sociology300.233
Psychology300.267
Overall-Tech and Engineering2100.276
Agriculture300.300
Architecture and Engineering300.200
Computer Science300.367
Electronics300.200
Energy and Power300.367
Materials300.233
Mechanical Engineering300.267

Fontes

1 fonte
Hugging FacePrimárioVersão 3843430d96f08bbfe5eb34c4321d57b8ef5a8412
huggingface.co/sbrzz/TinyLLaVA-Qwen2.5-0.5B-Instruct-dinov2-small/tree/3843430d96f08bbfe5eb34c4321d57b8ef5a8412

Verificado 30 de out.

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Repository files

File inventory only; completeness is unverified.

Artefatos de modelo

1 artefato

model.safetensors

safetensors · FP16 (tensor header) · 987 MB · SHA-256 ab9d8464c910…bef1 · Hugging Face

Download file

Trechos de fonte

3 trechos
Readme14 de ago.huggingface.co/sbrzz/TinyLLaVA-Qwen2.5-0.5B-Instruct-dinov2-small

--- license: apache-2.0 language: - zho - eng - fra - spa - por - deu - ita - rus - jpn - kor - vie - tha - ara base_model: - Qwen/Qwen2.5-0.5B-Instruct - facebook/dinov2-small pipeline_tag: visual-question-answering --- Pretrain stage only, 4630 epochs # Introduction We use the powerful [TinyLLaVA Factory](https://github.com/TinyLLaVA/TinyLLaVA_Factory) to create a super small image-text-to-text model. The goal is to make it possible to run LLaVA models on edge devices (with few gigabytes of memory). For LLM and vision tower, we choose [OpenELM-270M-Instruct](apple/OpenELM-270M-Instruct) and [facebook/dinov2-small](facebook/dinov2-small), respectively. [POPE](https://tinyllava-factory.readthedocs.io/en/latest/Evaluation.html#pope): | Category | # Samples | TP | FP | TN | FN | Accuracy | Precision | Recall | F1 Score | Yes Ratio | |-----------------|---------------|--------|--------|--------|--------|--------------|---------------|------------|--------------|---------------| | Adversarial | 3000 | 1312 | 1250 | 250 | 188 | 0.521 | 0.512 | 0.875 | 0.646 | 0.854 | | Popular | 3000 | 1312 | 1236 | 264 | 188 | 0.525 | 0.515 | 0.875 | 0.648 | 0.849 | | Random | 2910 | 1312 | 1185 | 225 | 188 | 0.528 | 0.525 | 0.875 | 0.656 | 0.858 | [TEXTVQA](https://tinyllava-factory.readthedocs.io/en/latest/Evaluation.html#textvqa) Samples 5000, Accuracy 0% (:-|) [SCIENCEQA](https://tinyllava-factory.readthedocs.io/en/latest/Evaluation.html#scienceqa) Samples 4241, Correct: -, Accuracy: -%, IMG-Accuracy: -% [MMMU](https://tinyllava-factory.readthedocs.io/en/latest/Evaluation.html#mmmu) | Category | # Samples | Accuracy | |---------------------------------|-----------|----------| | Overall | 900 | 0.280 | | Overall-Art and Design | 120 | 0.208 | | Art | 30 | 0.167 | | Art Theory | 30 | 0.200 | | Design | 30 | 0.367 | | Music | 30 | 0.100 | | Overall-Business | 150 | 0.213 | | Accounting | 30 | 0.100 | | Economics | 30 | 0.367 | | Finance | 30 | 0.200 | | Management | 30 | 0.233 | | Marketing | 30 | 0.167 | | Overall-Science | 150 | 0.300 | | Biology | 30 | 0.300 | | Chemistry | 30 | 0.133 | | Geography | 30 | 0.300 | | Math | 30 | 0.333 | | Physics | 30 | 0.433 | | Overall-Health and Medicine | 150 | 0.340 | | Basic Medical Science | 30 | 0.300 | | Clinical Medicine | 30 | 0.133 | | Diagnostics and Laboratory Med. |...

Note30 de out.huggingface.co/sbrzz/TinyLLaVA-Qwen2.5-0.5B-Instruct-dinov2-small

Source context: 14 downloads · 0 likes · Pipeline visual-question-answering · Repo sbrzz/TinyLLaVA-Qwen2.5-0.5B-Instruct-dinov2-small

Note14 de ago.huggingface.co/sbrzz/TinyLLaVA-Qwen2.5-0.5B-Instruct-dinov2-small

Source context: 11 downloads · 0 likes · Pipeline visual-question-answering · Repo sbrzz/TinyLLaVA-Qwen2.5-0.5B-Instruct-dinov2-small