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chanasia/typhoon-ocr1.5-2b-GGUF
typhoon-ocr1.5-2b-GGUF is a image-text-to-text model from chanasia. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for llama.cpp. The card lists the license as apache-2.0.
GGUF quantization of typhoon-ai/typhoon-ocr1.5-2b, a Thai/English document-OCR vision-language model built on Qwen3-VL-2B-Instruct.
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From the Hugging Face model README
GGUF quantization of typhoon-ai/typhoon-ocr1.5-2b, a Thai/English document-OCR vision-language model built on Qwen3-VL-2B-Instruct.
This is a vision-language model: you need both the model file and the mmproj
(multimodal projector) file. The model file alone will load, but it will not see images.
| File | Size | Notes |
|---|---|---|
typhoon-ocr1.5-2b-Q4_K_M-imat.gguf | 1.03 GiB | Language model, Q4_K_M with importance matrix |
typhoon-ocr1.5-2b-mmproj-Q8_0.gguf | 424 MiB | Vision encoder / projector — required |
The Q4_K_M weights were quantized with an importance matrix (imatrix) computed from a calibration set, which recovers some of the quality lost at 4 bits compared to a plain Q4_K_M of the same size.
llama-server \
-m typhoon-ocr1.5-2b-Q4_K_M-imat.gguf \
--mmproj typhoon-ocr1.5-2b-mmproj-Q8_0.gguf \
-c 8192 --host 0.0.0.0 --port 8080
Then post an image to /v1/chat/completions the usual way:
curl http://localhost:8080/v1/chat/completions \
-H 'Content-Type: application/json' \
-d '{
"messages": [{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": "data:image/png;base64,<BASE64>"}},
{"type": "text", "text": "Extract all text from this document as Markdown."}
]
}]
}'
llama-mtmd-cli \
-m typhoon-ocr1.5-2b-Q4_K_M-imat.gguf \
--mmproj typhoon-ocr1.5-2b-mmproj-Q8_0.gguf \
--image page.png \
-p "Extract all text from this document as Markdown."
Use a recent llama.cpp build — Qwen3-VL support landed relatively late.
Apache 2.0, inherited from the base model. See the base model card for the model's intended use and limitations.