- Bioinformatics ML
- NLP for academic notes, learning and productivity
- ML Python frameworks
- Blogging about this kind of contents (on CoderLegion: https://coderlegion.com/user/Astra+Bertelli; on DEV Community: https://dev.to/astrabert)
everything-ai v2.0.1: more AI power on your Desktop
What is everything-ai?
š¤ everything-ai is natively a multi-tasking agent, 100% local, that is able to perform several AI-related tasks
What's new?
š I am more than thrilled to introduce some new functionalities that were added since last release:
- šļøš Handle audio files or microphone recordings, classifying or transcribing them with almost every audio-classification and automatic-speech-recognition model on Hugging Face Hub. - š½ļø Generate video from text prompts with almost every text-to-video model on HuggingFace Hub (original architecture by [Vasiliy Katsyka](https://github.com/Vasiliy-katsyka)) - š§¬ Predict the 3D structure of proteins from their amino-acidic sequence, with EsmFold by AI at Meta ([demo](as-cle-bert/proteinviz) - šļø Finetune HF models on several downstream tasks with AutoTrain local integration (AutoTrain is developed by [Abhishek Thakur](https://github.com/abhishekkrthakur)) - š£ļø Unleash powerful LLMs and exploit larger database collections for RAG with the integration of Hugging Face Spaces API and Supabase PostgreSQL databases ([demo](https://huggingface.co/spaces/as-cle-bert/supabase-ai-chat))
Shout-outs to Hugging Face, Gradio, Docker, AI at Meta, Abhishek Thakur, Qdrant, LangChain and Supabase for making all of this possible! Inspired by: Jan, Cheshire Cat AI, LM Studio, Ollama and other awesome local AI solutions!
I'm thrilled to share the latest updates regarding the Space I built for protein 3D structure prediction (as-cle-bert/proteinviz): thanks to @lunarflu inputs, @osanseviero precious advice and @simonduerr's article "Visualize proteins on Hugging Face Spaces" (https://huggingface.co/blog/spaces_3dmoljs, go check it out!), I was able to finally display the 3D protein models directly on-browser, without any need for fancy downloads of big HTMLs!
Take a look to the attached video, that shows how everything works, and make sure to visit the GitHub repository (https://github.com/AstraBert/proteinviz: leave a little ā while you're there!)š„°
May you have fun and luck with your protein research!š§¬