Image-to-Text
Transformers
ONNX
Safetensors
vision-encoder-decoder
image-text-to-text
typst
math-ocr
formula-recognition
browser
grayscale
Instructions to use dbcccc/TypLens with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbcccc/TypLens with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("image-to-text", model="dbcccc/TypLens")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("dbcccc/TypLens") model = AutoModelForMultimodalLM.from_pretrained("dbcccc/TypLens", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,260 Bytes
f982163 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | # TypLens V1.1
V1.1 introduces a newly trained single-channel grayscale model and matched
training/browser preprocessing for printed formula images. It uses the final
33,544-step checkpoint and generates Typst directly.
- Full FP32 ONNX: **117.2 MB** of model weights.
- Compact dynamic INT8 ONNX: **33.1 MB**, 71.7% smaller.
- Native FP32 safetensors, tokenizer and configuration are available on
[Hugging Face](https://huggingface.co/dbcccc/TypLens).
- Both ONNX variants have completed desktop Edge/WASM smoke checks.
**Migration:** the input changes from three RGB channels to one luminance channel.
Adopt the preprocessing in INFERENCE.md and replace the encoder and decoder
together. Old V1 RGB preprocessing cannot be used with these weights.
The server FP32 checkpoint received 127/135 content passes on a reused development
set under assistant review. This is not independent accuracy or a compact-model
benchmark. The model card explains the scope and remaining errors.
Attach `typlens-v1.1-fp32-onnx.zip` and `typlens-v1.1-int8-onnx.zip` to this release.
Each asset includes its model pair, token bytes, preprocessing contract and license
notices. The release contains no training code. The MIT license and upstream
attribution are retained.
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