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 pytorch_model.bin from sivan22/hdd-words-ocr: direct link, hf CLI and curl.
- Browser
- Download file 968 MB
-
https://huggingface.co/sivan22/hdd-words-ocr/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sivan22/hdd-words-ocr/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sivan22/hdd-words-ocr/resolve/main/pytorch_model.bin
968 MB
- Xet hash:
- f155a2ce3fbc5bf0f88f2cd40f4667259320967702a001677e8b6cb28acb27a7
- Size of remote file:
- 968 MB
- SHA256:
- 0e1d801402fc739d497c6a7c5e70d58621e1d2875a28a7e3011cbfc972a9239c
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