Image-to-Text
Transformers
PyTorch
TensorBoard
Safetensors
Hebrew
vision-encoder-decoder
image-text-to-text
Instructions to use sivan22/hdd-words-ocr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sivan22/hdd-words-ocr 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="sivan22/hdd-words-ocr")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("sivan22/hdd-words-ocr") model = AutoModelForMultimodalLM.from_pretrained("sivan22/hdd-words-ocr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sivan22/hdd-words-ocr: direct link, hf CLI and curl.
- Browser
- Download file 3.77 kB
-
https://huggingface.co/sivan22/hdd-words-ocr/resolve/main/training_args.bin
- Command line
-
hf download hf://sivan22/hdd-words-ocr/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sivan22/hdd-words-ocr/resolve/main/training_args.bin
3.77 kB
- Xet hash:
- dd82a7f48a5ede73f47544436a8b0fe2fc88428946378976d8569d82bde32c01
- Size of remote file:
- 3.77 kB
- SHA256:
- d3e398b469f6b4c548cec0ec3b6dfc8464b129b5ae54af5d26a63321444e2055
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