Instructions to use Calligrapher2025/Calligrapher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Calligrapher2025/Calligrapher with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Calligrapher2025/Calligrapher", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Improve model card metadata: pipeline tag and library_name
Verified signatureThis PR improves the model card by updating the `pipeline_tag` to `text-to-image` for better discoverability, accurately reflecting the model's text-guided image customization capabilities. It also adds `library_name: transformers` to the metadata, as the model utilizes a `transformers`-based image encoder (`google/siglip-so400m-patch14-384`).1dc866c
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Add the gradio preview and user tips.
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Upload the preview of gradio demos.
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Update README.md
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Update README.md
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Update README.md
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Upload Calligrapher_bench_testing.zip
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Upload calligrapher.bin with huggingface_hub
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Update README.md
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Upload assets.
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Create README.md
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initial commit
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