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 model.safetensors from dbcccc/TypLens: direct link, hf CLI and curl.
- Browser
- Download file 117 MB
-
https://huggingface.co/dbcccc/TypLens/resolve/main/model.safetensors
- Command line
-
hf download hf://dbcccc/TypLens/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/dbcccc/TypLens/resolve/main/model.safetensors
117 MB
- Xet hash:
- 28ef74a99660609b89aacc6e6346fe80cc8b94e004cb04fb212ecb3405225c3b
- Size of remote file:
- 117 MB
- SHA256:
- d42cfd2da242a11ecdb1fe8727ee01e6896a116cd46f74357c4fdce90eebe788
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