Instructions to use melsiddieg/deepseek_ocr_arabic_v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use melsiddieg/deepseek_ocr_arabic_v5 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("melsiddieg/deepseek_ocr_arabic_v5", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use melsiddieg/deepseek_ocr_arabic_v5 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for melsiddieg/deepseek_ocr_arabic_v5 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for melsiddieg/deepseek_ocr_arabic_v5 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for melsiddieg/deepseek_ocr_arabic_v5 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="melsiddieg/deepseek_ocr_arabic_v5", max_seq_length=2048, )
- Xet hash:
- a803a41234b4d107c102ee43b5677bfec0f9b4c5e2fc2b65e9e4f06a893254fe
- Size of remote file:
- 6.67 GB
- SHA256:
- 931a38066ac49d80dad2340e86551c771e376b54bf3c93d1fc5bc5b2dbb0744a
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