Instructions to use MixTex/tiny-ZhEn-for-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MixTex/tiny-ZhEn-for-onnx 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="MixTex/tiny-ZhEn-for-onnx")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("MixTex/tiny-ZhEn-for-onnx") model = AutoModelForMultimodalLM.from_pretrained("MixTex/tiny-ZhEn-for-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from MixTex/tiny-ZhEn-for-onnx: direct link, hf CLI and curl.
- Browser
- Download file 228 Bytes
-
https://huggingface.co/MixTex/tiny-ZhEn-for-onnx/resolve/refs%2Fpr%2F1/preprocessor_config.json
- Command line
-
hf download hf://MixTex/tiny-ZhEn-for-onnx@refs/pr/1/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/MixTex/tiny-ZhEn-for-onnx/resolve/refs%2Fpr%2F1/preprocessor_config.json
228 Bytes
| { | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_processor_type": "ViTImageProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 448, | |
| "width": 448 | |
| } | |
| } | |