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
Download onnx/int8/encoder.onnx from dbcccc/TypLens: direct link, hf CLI and curl.
- Browser
- Download file 24.5 MB
-
https://huggingface.co/dbcccc/TypLens/resolve/main/onnx/int8/encoder.onnx
- Command line
-
hf download hf://dbcccc/TypLens/onnx/int8/encoder.onnx
-
curl -L -o encoder.onnx https://huggingface.co/dbcccc/TypLens/resolve/main/onnx/int8/encoder.onnx
24.5 MB
- Xet hash:
- cc32f2f81167761bec2c7e181e4d96ce74bb46b9c6a002c72a375154f9fcde8f
- Size of remote file:
- 24.5 MB
- SHA256:
- 844a4aee1e22ca0a71d0a5b29c7d9fec00f976f7528a50af2ce1c141deb37ab1
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