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@@ -9,7 +9,7 @@ license: mit
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  2. [Uses](#uses)
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  3. [Training Details](#training-details)
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  4. [Evaluation](#evaluation)
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- 5. [Acknolwedgements](#acknowledgements)
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  6. [Citation](#citation)
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  7. [How To Get Started With the Model](#how-to-get-started-with-the-model)
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  # Uses
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- As per the original OpenAI CLIP models, this model is intended as a research output for research communities. We hope that this model will enable researchers to better understand and explore zero-shot, arbitrary image classification. We also hope it can be used for interdisciplinary studies of the potential impact of such model.
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  The OpenAI CLIP paper includes a discussion of potential downstream impacts to provide an example for this sort of analysis. Additionally, the LAION-5B blog (https://laion.ai/blog/laion-5b/) and upcoming paper include additional discussion as it relates specifically to the training dataset.
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  2. [Uses](#uses)
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  3. [Training Details](#training-details)
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  4. [Evaluation](#evaluation)
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+ 5. [Acknowledgements](#acknowledgements)
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  6. [Citation](#citation)
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  7. [How To Get Started With the Model](#how-to-get-started-with-the-model)
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  # Uses
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+ As per the original [OpenAI CLIP model card](https://github.com/openai/CLIP/blob/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1/model-card.md), this model is intended as a research output for research communities. We hope that this model will enable researchers to better understand and explore zero-shot, arbitrary image classification. We also hope it can be used for interdisciplinary studies of the potential impact of such model.
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  The OpenAI CLIP paper includes a discussion of potential downstream impacts to provide an example for this sort of analysis. Additionally, the LAION-5B blog (https://laion.ai/blog/laion-5b/) and upcoming paper include additional discussion as it relates specifically to the training dataset.
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