• ⚡️ Hi, I’m @raynardj, I code fast, automate hard problems/
• 🗡 deep learning (especially play with tensor part), movie trivials, books
• ⭐️ I’m seek collaboration on automated DL tools

• Progerssion system: Expert. 2x🥉 medals, 1x🥈 medals kaggle profile page

• Taichi-Engine: Automated UI based multimodal DL tool. Documentation, github here, or the following video explain the idea.
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• glow-cli: a commandline tool that can boost your efficiency pip install glow-cli, for now the code is close sourced. eg. you can do cool stunts in your terminal by asking
  • g llm "explain what's the name pattern under $(ls /dev) and which file might be the usb flash drive?"
  • g llm "how do I mount one of the pod with keyword 'abc', the pods are $(kubectl get pods)"
• Category: Rust accelerated category translation toolset: Category pip install category, based on the Rust core part of the library pip install rust-category also by Ray
• Language Annotation library pip install langhuan
• python4ml: The library I kept accumulating the tutorial while teaching DL at cokerbunker(a coding community)
• unpackai: a library I lead for teaching at unpackai.
• As a person who's deeply interested in history and actual archaeological text, I put up and assortment of models to help accelerate ancient Chinese research: yuan, many of the model uploaded to huggingface's model hub.
• Docs in forms of github pages show casing some of the experiments I did in Genomicare

• Huggingface profile, it's before the chatgpt era, some for medical research paper extraction, some for ancient chinese. Most space haven't catch up with maintenance much.

I TALK SLOW, PLESAE WATCH IN 1.75x+, just trying to record ideas, and understanding

• Visualize Embedding Movement in 10 Minutes
• LLM in your command line glow-cli
• A chrome extension using NLPsa system - BioInformatics Reading Assistant
• Tutorial to langhuan (mentioned above): tutorial: Label NER, classification for nlp (text) tasks

• Clippy! Paper on Youtube Recommender Solving Loss Divergence
• 🍦VanillaNet Deep Dive in 14 Minutes
• Why Transformers for NLP, but not LSTM