blip-caption
sgpt
| blip-caption | sgpt | |
|---|---|---|
| 2 | 3 | |
| 101 | 164 | |
| - | - | |
| 4.0 | 9.7 | |
| 8 months ago | 1 day ago | |
| Python | Go | |
| - | MIT License |
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.
blip-caption
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Bash One-Liners for LLMs
I've been gleefully exploring the intersection of LLMs and CLI utilities for a few months now - they are such a great fit for each other! The unix philosophy of piping things together is a perfect fit for how LLMs work.
I've mostly been exploring this with my https://llm.datasette.io/ CLI tool, but I have a few other one-off tools as well: https://github.com/simonw/blip-caption and https://github.com/simonw/ospeak
I'm puzzled that more people aren't loudly exploring this space (LLM+CLI) - it's really fun.
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MetaCLIP – Meta AI Research
I suggest trying BLIP for this. I've had really good results from that.
https://github.com/salesforce/BLIP
I built a tiny Python CLI wrapper for it to make it easier to try: https://github.com/simonw/blip-caption
sgpt
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Aider: AI pair programming in your terminal
I feel only a bit bad when deploying a billion dollar machine model to ask "how to rename a git a branch" every other week. Its the easiest way (https://github.com/tbckr/sgpt) compared to reading the manual, but reading the manual is the right way.
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Linux Text Manipulation
I've been saving a lot of time in the terminal recently with shell-gpt (https://github.com/tbckr/sgpt):
$ sgpt -s "The command 'sp current' outputs -
Bash One-Liners for LLMs
https://github.com/tbckr/sgpt
I totally agree with LLM+CLI are perfect fit.
One pattern I used recently was httrack + w3m dump + sgpt images with gpt vision to generate a 278K token specific knowledge base with a custom perl hack for a RAG that preserved the outline of the knowledge.
Which brings me to my question for you - have you seen anything unix philosophy aligned for processing inputs and doing RAG locally?
What are some alternatives?
MetaCLIP - ICLR2024 Spotlight: curation/training code, metadata, distribution and pre-trained models for MetaCLIP; CVPR 2024: MoDE: CLIP Data Experts via Clustering
geppetto - golang GPT3 tooling
NumPyCLIP - Pure NumPy implementation of https://github.com/openai/CLIP
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
BLIP - PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
promptos - A collection of promptos for thirdparty packages
open_clip - An open source implementation of CLIP.
ospeak - CLI tool for running text through OpenAI Text to speech
autodistill-metaclip - MetaCLIP module for use with Autodistill.
scrapio - SMWCentral Scraper / Auto-patcher for Super Mario World romhacks
unstructured - Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.