gauravvij137

Running a GGUF model locally usually means writing custom inference code or wrestling with llama.cpp's CLI flags every time you want to test something. Existing OpenAI-compatible servers often require Docker, complex…

I built FC-Eval to have a repeatable way to evaluate how well different LLMs handle function calling before using them in agent workflows. It runs models through 30 test cases covering single-turn, multi-turn, and…

I got tired of picking LLMs based on vibes and leaderboards that don't reflect real workloads, so I built this. You describe a task in plain English. The tool generates a test suite for that specific task, discovers…

Built a small agent that can explore a GitHub repository, understand it in-depth, and answer questions about the codebase. The idea is simple. When you open a new repo, most of the time goes into figuring out: - Where…

We asked Neo AI to build a small voice assistant pipeline that runs with low latency on CPU instead of requiring a GPU. The goal was to see how responsive a LLM → speech system can be on normal laptops or edge devices.…

Building reliable LLM systems often means not trusting a single model. We open-sourced LLM Council: https://github.com/abhishekgandhi-neo/llm_council It’s a small framework we internally built with Neo to run multiple…

Founder here. I built NEO, an AI agent designed specifically for AI and ML engineering workflows, after repeatedly hitting the same wall with existing tools: they work for short, linear tasks, but fall apart once…

NEO is an autonomous machine learning engineering AI agent capable of implementing complex ML tasks - From data cleaning, preprocessing, handling structural issues to model exploration, training, optimization with its…

A consolidated API to fine-tune whisper models for scalable and cost efficient transcription and translation of audio files.