We have released an implementation of OpenAI’s CLIP model that completely removes the need for PyTorch, enabling you to quickly and seamlessly install this fantastic model in production and even possibly on edge devices.
Deploying state-of-the-art machine learning models can often lead to a myriad of issues due to the dependencies of the more salient packages - most commonly PyTorch and TensorFlow. At Lakera, we have released an implementation of OpenAI’s CLIP model that completely removes the need for PyTorch, enabling you to quickly and seamlessly install this fantastic model in production and on edge devices.
CLIP (Contrastive Language-Image Pre-Training) is powering some of the most exciting image to text applications out there right now. It’s a neural network trained on a variety of (image, text) pairs. It can be instructed in natural language to predict the most relevant text snippet, given an image, without directly optimizing for the task, similarly to the zero-shot capabilities of GPT-2 and 3. There are three main components that comprise this model:
The main issue we have found is that all three of these pieces utilise PyTorch - so we decided to simplify things for you!
We achieved this with the following steps:
Try it out! Don’t forget to give it a star and reach out if you have any feedback!
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