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dnhkng/RYS-Medium
RYS-Medium is a text generation model from dnhkng. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
This is a new kind of model optimization. A paper on the technique is currently being written.
Downloads ยท 30 days
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From the Hugging Face model README
This is a new kind of model optimization. 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.
This code snippets show how to get quickly started with running the model on a GPU:
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
torch.random.manual_seed(0)
model_id = "dnhkng/Medium"
model = AutoModelForCausalLM.from_pretrained(
model_id,
device_map="cuda",
torch_dtype="auto",
trust_remote_code=True,
)
tokenizer = AutoTokenizer.from_pretrained(model_id)
messages = [
{"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"},
{"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."},
{"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"},
]
pipe = pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
)
generation_args = {
"max_new_tokens": 500,
"return_full_text": False,
"temperature": 0.0,
"do_sample": False,
}
output = pipe(messages, **generation_args)
print(output[0]['generated_text'])
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 25.94 |
| IFEval (0-Shot) | 44.06 |
| BBH (3-Shot) | 47.73 |
| MATH Lvl 5 (4-Shot) | 7.78 |
| GPQA (0-shot) | 10.40 |
| MuSR (0-shot) | 8.73 |
| MMLU-PRO (5-shot) | 36.96 |
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
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
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 25.94 |
| IFEval (0-Shot) | 44.06 |
| BBH (3-Shot) | 47.73 |
| MATH Lvl 5 (4-Shot) | 7.78 |
| GPQA (0-shot) | 10.40 |
| MuSR (0-shot) | 8.73 |
| MMLU-PRO (5-shot) | 36.96 |