Model reference · open weights

meiki.text.detect

meiki.text.detect is an open-weight language model from rtr46, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.

LLMs rtr46 1 variants 51k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What meiki.text.detect is

Official GitHub Repository: meikiocr This model is a core component of the meikiocr pipeline. For the full implementation, command-line script, and documentation, please see the official GitHub repository. meiki.text.detect.v0.1 meiki.text.detect.v0.1 is an update to meiki.text.detect.v0 (see below): - meiki.text.detect.v0.1 is a new state-of-the-art, open weight text detection model for video games beating text detection models like PaddleOCR - while it is still based on D-FINE detector, it uses mobilenet v4 small as backbone instead of hgnet v2 - v0.1 comes in 2 variants: v0.1.960x544 and v0.1.320x192. unlike v0 both v0.1 variants share the same architecture, but are trained on different resolutions - v0.1 models increase focus on video game text detection and are limited to 64 detected boxes, increasing efficency for this use case (making them less suitable for manga text detection out of the box) - v0.1.960x544 and v0.1.320x192 have better accuracy and lower latency than small.v0 and tiny.v0 respectively meiki.text.detect.v0 experimental text detection models with focus on low latency. trained on japanese video games and manga. model versions: - tiny: good for images with only few textlines (e.g. visual novels). ~30ms latency on CPU. ~3ms on GPU. - small: better for cases with many textlines (e.g. manga). ~70ms latency on CPU. ~7ms on GPU. fine-tune of https://github.com/Peterande/D-FINE examples visual novel manga

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

Makerrtr46
TypeLanguage models
Variants1
Runs withtensorrt
Released2025-10-21
Popularity51k downloads / month
Likes3
LicenceOpen, with conditions

How it works

How language models work

Your prompttext / messagesTransformerattention over tokensNext-token loopgenerate + streamResponsetext · tool callsA language model reads your tokens and predicts the next one, again and again, streaming the reply back.

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

VariantParamsPrecisionVRAMFits 16 GBWeights
meiki.text.detect.v0BF16Weights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys meiki-text-detect for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (meiki-text-detect below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"meiki-text-detect","messages":[{"role":"user","content":"Hello"}]}'

Details

Languages, data & research

Languages

en ja

Tags

tensorrt onnx text-detection textline_detection computer-vision japanese ocr OCR image-to-text en ja

Licence

Open, with conditions

Open weights under lgpl-3.0, which carries conditions (e.g. attribution or an acceptable-use clause). Worth a read before production use — we can walk you through it. Read the licence ↗

Sources

Weights & code

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