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nakamura196/yigdzin1-gguf
yigdzin1-gguf is a machine learning model from nakamura196. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
GGUF conversion of BDRC/tibetan-ocr ("Yigdzin-1"), a Tibetan OCR vision-language model fine-tuned from PaddlePaddle/PaddleOCR-VL-1.6, for use with llama.cpp / llama-server (mtmd multimodal support). Used by the
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From the Hugging Face model README
GGUF conversion of BDRC/tibetan-ocr
("Yigdzin-1"), a Tibetan OCR vision-language model fine-tuned from
PaddlePaddle/PaddleOCR-VL-1.6,
for use with llama.cpp / llama-server
(mtmd multimodal support). Used by the
local-ocr desktop app.
yigdzin1.gguf — the language model (Q8_0-equivalent precision inherited from
the source checkpoint's conversion; same conversion path as
PaddlePaddle/PaddleOCR-VL-1.6-GGUF)yigdzin1-mmproj.gguf — the vision projector (--mmproj)Converted with a stock (unmodified) llama.cpp build (b10776) using its
conversion/ernie.py PaddleOCR-VL converter, with one compatibility fix: this
checkpoint ships processor_config.json with size.shortest_edge/size.longest_edge
instead of the flat min_pixels/max_pixels keys the base PaddleOCR-VL-1.6 uses,
which the stock converter doesn't handle. No change was made to inference-time
behavior — the produced GGUF carries no non-standard metadata and loads/runs
identically to any other PaddleOCR-VL-arch GGUF on stock llama-server.
(An earlier, separate experiment explored whether Yigdzin-1's image-token positional encoding needs a non-standard "sequential" mode at inference time — relevant for whole-page images. It was found unnecessary for the line-level crops this conversion targets; see the source app's repository for details.)
llama-server -m yigdzin1.gguf --mmproj yigdzin1-mmproj.gguf
Then send a chat-completion request with an image (line crop) and the prompt
"Extract all Tibetan text.".
Apache-2.0, inherited from BDRC/tibetan-ocr.