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This is a new kind of model optimization. This model is based on Meta-Llama-3.1-8B.

A paper on the technique is currently being written.

This research was supported with hardware from the appliedAI Institute, whose goal is to generate and communicate high-quality knowledge about trustworthy AI.

Quickstart

import transformers
import torch

model_id = "meta-llama/Meta-Llama-3.1-8B"

pipeline = transformers.pipeline(
    "text-generation", model=model_id, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto"
)

pipeline("Hey how are you doing today?")

SHAMELESS ADVERTISING BREAK

I’m on the hunt for new challenges and a chance to dive into some exciting research opportunities. Oh, and did I mention I just snagged a top spot on the Open LLM leaderboard? πŸŽ‰

Profile

Innovation enthusiast, AI strategist, and interdisciplinary-tech nerd – that's me! With over a decade of experience in research and project management, my professional journey has been largely shaped by my passion for artificial intelligence and its potential to transform various industries. With a solid background in artificial intelligence and machine learning, coupled with a knack for innovation and problem-solving (and a healthy dose of curiosity), I'm excited to bring my skills to a new team.

Originally from Australia, where I earned my degrees in Organic Chemistry and Biochemistry, I moved to Germany in 2004. My academic pursuit continued with a PhD. in Chemistry at the Max Planck Institute of Biochemistry. Today, I leverage my robust educational background and diverse industry experience to drive AI innovations in a wide range of applications. Hobbies? Lots: I've also built the world's most powerful espresso machine and am working to bring GLaDOS to life.


I'm based out of Munich, Germany, but I would be interested in working remotely for a team with more compute than my 2x 4090s πŸš€

Reach out via LinkedIn - Dr David Noel Ng

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 26.44
IFEval (0-Shot) 76.85
BBH (3-Shot) 31.09
MATH Lvl 5 (4-Shot) 11.33
GPQA (0-shot) 2.35
MuSR (0-shot) 7.68
MMLU-PRO (5-shot) 29.33
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Evaluation results