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/decoder.onnx from dbcccc/TypLens: direct link, hf CLI and curl.
- Browser
- Download file 8.64 MB
-
https://huggingface.co/dbcccc/TypLens/resolve/main/onnx/int8/decoder.onnx
- Command line
-
hf download hf://dbcccc/TypLens/onnx/int8/decoder.onnx
-
curl -L -o decoder.onnx https://huggingface.co/dbcccc/TypLens/resolve/main/onnx/int8/decoder.onnx
8.64 MB
- Xet hash:
- 4c570c715b54ee405be03d98c272655903b1d0b388fcff58df3cfa2c74771faa
- Size of remote file:
- 8.64 MB
- SHA256:
- 9bf4bfd55786c45b7fe92221c0b752c70bb405d028f5e7d4f066814e839b70df
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