Flova/omr_transformer β GGUF (for CrispEmbed)
GGUF conversions of Flova/omr_transformer,
an end-to-end handwritten / whiteboard Optical Music Recognition model that
transcribes monophonic "simple notes" staff images into
LilyPond note strings (e.g. c'2 a''8 c''8 r4 c'1 β¦).
It is the only permissively-licensed (Apache-2.0) end-to-end handwritten-music
OMR model, and complements the printed-music engines
(SMT,
Polyphonic-TrOMR) already in CrispEmbed.
Architecture
A Donut Vision-Encoder-Decoder (~143M params):
- Encoder β DonutSwin (Swin-Base scale): patch 4, window 10, embed_dim 128,
depths
[2,2,14,2], heads[4,8,16,32], hidden 1024, input 583Γ409. - Decoder β 4-layer pre-norm mBART: d_model 1024, 16 heads, ffn 4096,
vocab 75, learned positions (offset +2), scale-embedding (Γβ1024), GELU.
decoder_start/bos= 56 (<s>),eos= 54 (</s>),pad= 55.
Files
| File | Size | Notes |
|---|---|---|
flova-f32.gguf |
573 MB | Full precision (reference). |
flova-q8_0.gguf |
162 MB | Recommended. Decodes byte-identically to the f32 / HF model on the sample images. |
The Swin encoder is all-linear, so q8_0 needs no keep-guard: the patch-embed
convolution and the relative-position index table are kept at F32 automatically.
Parity
Validated per-stage against the HF reference (CPU): every stage cosine
1.000000 (encoder stages + output, all 4 decoder blocks, logits), 40/40
teacher-forced argmax agreement, and byte-exact greedy decode matching the
model card. q8_0 reproduces the exact LilyPond output on all three sample
images.
Usage (CrispEmbed)
# auto-downloads flova-q8_0.gguf on first use
crispembed --model flova --ocr score.png
# β c'2 a''8 c''8 r4 c'1 e'8 c'8 c'8 a''8 f'4 a'8 c'8
or with an explicit path:
crispembed -m flova-q8_0.gguf --ocr score.png
CrispEmbed: https://github.com/CrispStrobe/CrispEmbed
License & attribution
Apache-2.0, inherited from the source model.
- Model: Flova/omr_transformer
- Blueprint / project: UHHRobotics22-23/robot_project (marimbabot_vision)
These are format conversions only; all model weights and credit belong to the original authors.
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Base model
Flova/omr_transformer