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")# 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 native-output.json from dbcccc/TypLens: direct link, hf CLI and curl.
- Browser
- Download file 213 Bytes
-
https://huggingface.co/dbcccc/TypLens/resolve/main/native-output.json
- Command line
-
hf download hf://dbcccc/TypLens/native-output.json
-
curl -L -o native-output.json https://huggingface.co/dbcccc/TypLens/resolve/main/native-output.json
213 Bytes
| { | |
| "model_name": "TypLens V1.1", | |
| "version": "v1.1", | |
| "output_language": "typst", | |
| "inference_conversion": "none", | |
| "source_model_sha256": "d42cfd2da242a11ecdb1fe8727ee01e6896a116cd46f74357c4fdce90eebe788" | |
| } | |