LLM content classification with only prompt engineering
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Updated
Mar 31, 2024 - Python
LLM content classification with only prompt engineering
A user-friendly interface for interacting with my FFmpeg Fork with new CLIP and CLAP Classification functionallity, along with an analysis script for in-depth video comprehension.
This repository contains the source code for a complete, end-to-end MLOps project that automatically trains, evaluates, and deploys a machine learning model to classify Reddit content as Safe-For-Work (SFW) or Not-Safe-For-Work (NSFW).
A new package that processes user-submitted text descriptions of gift-wrapped parcels and returns a structured analysis of the contents, wrapping quality, and potential surprises. It uses pattern matc
Extensive analysis of user guides in Swiss government-to-citizen software, correlating guide features with canton socio-economic factors.
Production-ready Telegram forwarder with per-category rules, session-based routing, Cornix-style UI, deduplication, link policies, and movie/series classification (MongoDB + Motor).
🎁 Analyze gift-wrapped parcels with this Python package, revealing their contents and surprises for games, events, or creative prompts.
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