This is a new kind of model optimization. This model is based on Meta's Llama-3 70B Instruct.
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.
Usage with Transformers AutoModelForCausalLM
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "dnhkng/RYS-Llama3.1-Large"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
device_map="auto",
)
messages = [
{"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
{"role": "user", "content": "Who are you?"},
]
input_ids = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
return_tensors="pt"
).to(model.device)
terminators = [
tokenizer.eos_token_id,
tokenizer.convert_tokens_to_ids("<|eot_id|>")
]
outputs = model.generate(
input_ids,
max_new_tokens=256,
eos_token_id=terminators,
do_sample=True,
temperature=0.6,
top_p=0.9,
)
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))
ADVERTISING BREAK
Iโm 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? ๐
Profile
Innovation enthusiast, AI strategist, and interdisciplinary-tech nerd โ 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 ๐
Reach out via LinkedIn - Dr David Noel Ng
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 41.60 |
IFEval (0-Shot) | 84.92 |
BBH (3-Shot) | 55.41 |
MATH Lvl 5 (4-Shot) | 28.40 |
GPQA (0-shot) | 16.55 |
MuSR (0-shot) | 17.09 |
MMLU-PRO (5-shot) | 47.21 |
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Model tree for dnhkng/RYS-Llama3.1-Large
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard84.920
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard55.410
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard28.400
- acc_norm on GPQA (0-shot)Open LLM Leaderboard16.550
- acc_norm on MuSR (0-shot)Open LLM Leaderboard17.090
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard47.210