Mlx_clip Alternatives

Similar projects and alternatives to mlx_clip

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• minGPT

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  A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

• InfluxDB

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  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• open_clip

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  An open source implementation of CLIP.

  

• frawk

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• Megatron-LM

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• mapscii

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  🗺 MapSCII is a Braille & ASCII world map renderer for your console - enter => telnet mapscii.me <= on Mac (brew install telnet) and Linux, connect with PuTTY on Windows

• datafaker

  16 1,038 9.4 Java mlx_clip VS datafaker

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• SaaSHub

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• canopy

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  Retrieval Augmented Generation (RAG) framework and context engine powered by Pinecone

  

• dify

  13 28,957 9.9 TypeScript mlx_clip VS dify

  Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.

  

• opengist

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  Self-hosted pastebin powered by Git, open-source alternative to Github Gist.

• pico

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• doom-checkboxes

  7 173 0.0 JavaScript mlx_clip VS doom-checkboxes

  🕹️ DOOM rendered via checkboxes in a web browser.

• examples

  6 2,465 9.3 Jupyter Notebook mlx_clip VS examples

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• carapace-bin

  6 711 9.8 Go mlx_clip VS carapace-bin

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• parquet-wasm

  6 471 9.0 Rust mlx_clip VS parquet-wasm

  Rust-based WebAssembly bindings to read and write Apache Parquet data

• mwparserfromhell

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• api-samples

  4 5,272 0.0 Java mlx_clip VS api-samples

  Code samples for YouTube APIs, including the YouTube Data API, YouTube Analytics API, and YouTube Live Streaming API. The repo contains language-specific directories that contain the samples.

  

• maxtext

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• paxml

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  Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.

  

• univer

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• SaaSHub

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