Text-to-Image
Transformers
PyTorch
Chinese
altclip
zero-shot-image-classification
stable-diffusion
stable-diffusion-diffusers
Chinese
multilingual
English(En)
Chinese(Zh)
Spanish(Es)
French(Fr)
Russian(Ru)
Japanese(Ja)
Korean(Ko)
Arabic(Ar)
Italian(It)
Instructions to use BAAI/AltCLIP-m9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/AltCLIP-m9 with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("BAAI/AltCLIP-m9") model = AutoModelForZeroShotImageClassification.from_pretrained("BAAI/AltCLIP-m9") - Notebooks
- Google Colab
- Kaggle
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README.md
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The AltCLIP-m9 model can provide support for the AltDiffusion-m9 model in this project. Specific information on the AltDiffusion model can be found in [this tutorial](https://github.com/FlagAI-Open/FlagAI/tree/master/examples/AltDiffusion/README.md).
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The model code has been open sourced on [FlagAI](https://github.com/FlagAI-Open/FlagAI/tree/master/examples/AltCLIP) and the weights are located on [modelhub](https://model.baai.ac.cn/model-detail/
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## 引用
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关于AltCLIP,我们已经推出了相关报告,有更多细节可以查阅,如对您的工作有帮助,欢迎引用。
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The AltCLIP-m9 model can provide support for the AltDiffusion-m9 model in this project. Specific information on the AltDiffusion model can be found in [this tutorial](https://github.com/FlagAI-Open/FlagAI/tree/master/examples/AltDiffusion/README.md).
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The model code has been open sourced on [FlagAI](https://github.com/FlagAI-Open/FlagAI/tree/master/examples/AltCLIP) and the weights are located on [modelhub](https://model.baai.ac.cn/model-detail/100077). We also provide scripts for fine-tuning, inference, and validation, so feel free to try them out.
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## 引用
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关于AltCLIP,我们已经推出了相关报告,有更多细节可以查阅,如对您的工作有帮助,欢迎引用。
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