Queryable VS Chinese-CLIP

Compare Queryable vs Chinese-CLIP and see what are their differences.

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Queryable Chinese-CLIP
5 1
2,424 3,590
- 11.3%
7.9 7.6
15 days ago 5 months ago
Swift Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Queryable

Posts with mentions or reviews of Queryable. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-13.

Chinese-CLIP

Posts with mentions or reviews of Chinese-CLIP. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Queryable and Chinese-CLIP you can also consider the following projects:

clip-retrieval - Easily compute clip embeddings and build a clip retrieval system with them

dream-creator - Quickly and easily create / train a custom DeepDream model

natural-language-image-search - Search photos on Unsplash using natural language

deepsparse - Sparsity-aware deep learning inference runtime for CPUs

aphantasia - CLIP + FFT/DWT/RGB = text to image/video

FARM - :house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.

natural-language-youtube-search - Search inside YouTube videos using natural language

PyTorch_CIFAR10 - Pretrained TorchVision models on CIFAR10 dataset (with weights)

Awesome-CLIP - Awesome list for research on CLIP (Contrastive Language-Image Pre-Training).

autodistill-metaclip - MetaCLIP module for use with Autodistill.

MoTIS - [NAACL 2022]Mobile Text-to-Image search powered by multimodal semantic representation models(e.g., OpenAI's CLIP)

transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.