This is a new kind of model optimization.
This model is based on Qwen2-72B
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
Here provides a code snippet with apply_chat_template to show you how to load the tokenizer and model and how to generate contents.
1from transformers import AutoModelForCausalLM, AutoTokenizer
2device = "cuda" # the device to load the model onto
3
4model = AutoModelForCausalLM.from_pretrained(
5 "dnhkng/RYS-XLarge",
6 torch_dtype="auto",
7 device_map="auto"
8)
9tokenizer = AutoTokenizer.from_pretrained("dnhkng/RYS-XLarge")
10
11prompt = "Give me a short introduction to large language model."
12messages = [
13 {"role": "system", "content": "You are a helpful assistant."},
14 {"role": "user", "content": prompt}
15]
16text = tokenizer.apply_chat_template(
17 messages,
18 tokenize=False,
19 add_generation_prompt=True
20)
21model_inputs = tokenizer([text], return_tensors="pt").to(device)
22
23generated_ids = model.generate(
24 model_inputs.input_ids,
25 max_new_tokens=512
26)
27generated_ids = [
28 output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
29]
30
31response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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? 🎉
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 🚀
