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README.md ADDED
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+ ---
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+ license: mit
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+ model-index:
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+ - name: RYS-XLarge
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+ results:
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: IFEval (0-Shot)
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+ type: HuggingFaceH4/ifeval
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: inst_level_strict_acc and prompt_level_strict_acc
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+ value: 79.96
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+ name: strict accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dnhkng/RYS-XLarge
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: BBH (3-Shot)
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+ type: BBH
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+ args:
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+ num_few_shot: 3
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+ metrics:
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+ - type: acc_norm
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+ value: 58.77
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dnhkng/RYS-XLarge
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MATH Lvl 5 (4-Shot)
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+ type: hendrycks/competition_math
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+ args:
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+ num_few_shot: 4
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+ metrics:
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+ - type: exact_match
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+ value: 38.97
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+ name: exact match
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dnhkng/RYS-XLarge
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: GPQA (0-shot)
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+ type: Idavidrein/gpqa
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: acc_norm
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+ value: 17.9
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+ name: acc_norm
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dnhkng/RYS-XLarge
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MuSR (0-shot)
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+ type: TAUR-Lab/MuSR
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: acc_norm
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+ value: 23.72
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+ name: acc_norm
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dnhkng/RYS-XLarge
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MMLU-PRO (5-shot)
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+ type: TIGER-Lab/MMLU-Pro
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+ config: main
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+ split: test
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 49.2
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=dnhkng/RYS-XLarge
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+ name: Open LLM Leaderboard
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+ ---
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+
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+ This is a new kind of model optimization.
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+ This model is based on MaziyarPanahi/calme-2.1-qwen2-72b, which was tuned from Qwen2-72B.
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+
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+ A paper is currently being written on the technique. Special thanks to my wife, for putting up with me coding in the basement for too many evenings and weekends for months!
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+
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+ ## Quickstart
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+
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+ Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ device = "cuda" # the device to load the model onto
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+
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+ model = AutoModelForCausalLM.from_pretrained(
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+ "dnhkng/RYS-XLarge",
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+ torch_dtype="auto",
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+ device_map="auto"
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+ )
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+ tokenizer = AutoTokenizer.from_pretrained("dnhkng/RYS-XLarge")
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+
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+ prompt = "Give me a short introduction to large language model."
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+ messages = [
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+ {"role": "system", "content": "You are a helpful assistant."},
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+ {"role": "user", "content": prompt}
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+ ]
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+ text = tokenizer.apply_chat_template(
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+ messages,
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+ tokenize=False,
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+ add_generation_prompt=True
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+ )
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+ model_inputs = tokenizer([text], return_tensors="pt").to(device)
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+
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+ generated_ids = model.generate(
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+ model_inputs.input_ids,
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+ max_new_tokens=512
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+ )
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+ generated_ids = [
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+ output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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+ ]
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+
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+ response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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+ ```
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+ # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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+ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_dnhkng__RYS-XLarge)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |44.75|
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+ |IFEval (0-Shot) |79.96|
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+ |BBH (3-Shot) |58.77|
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+ |MATH Lvl 5 (4-Shot)|38.97|
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+ |GPQA (0-shot) |17.90|
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+ |MuSR (0-shot) |23.72|
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+ |MMLU-PRO (5-shot) |49.20|
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+
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+ ___________________________________
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+ # *ADVERTISING BREAK*
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+
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+ 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? 🎉
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+
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+
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+
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+ ## CV - Dr David Noel Ng
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+
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+
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+ #### Profile
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+ Innovation enthusiast, AI-strategist, and interdisciplinary-tech nerd – that's me in a nutshell. 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.
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+
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+ 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 Ph.D. 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](https://github.com/dnhkng/GlaDOS).
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+
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+
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+ ___________________________________
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+ ### PROFESSIONAL EXPERIENCE
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+ #### SENIOR GLOBAL INNOVATION STRATEGIST - ARTIFICIAL INTELLIGENCE
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+ #### Munich Re | Munich | 05/2023 - Now
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+
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+ As a Senior Global Innovation Strategist at Munich Re, my passion is in steering AI/ML strategies, maximizing project impact, and advancing the use of cutting-edge technology. I built the AI Accelerator, which drives the rapid and structured development of AI use-case Implementations.
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+ #### AI CONSULTANT - LEAD AI ENGINEER
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+ #### appliedAI UTUM | Munich | 04/2019 - 04/2023
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+
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+ In my tenure at appliedAI, I held a leadership role where I spearheaded the successful development and execution of various AI/ML proof-of-concept (POC) and minimum viable product (MVP) projects. I utilized a hands-on approach to drive ideation, planning, and delivery of these solutions for our clients.
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+
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+ - AI-Controlled Imaging: Directed a PoC of an AI-Controlled Electron Microscope using Reinforcement Learning for a premier imaging company.
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+ - Anomaly Detection: Oversaw development of security systems utilizing anomaly detection, integrating diverse technologies to boost client security at the Munich Security Conference..
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+ - Project Optimization: Implemented AlphaZero-based Graph Optimization for project management in the Nuclear Energy sector.
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+ - Food Safety: Delivered a PoC for industrial food safety equipment, significantly improving detection sensitivity.
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+ - NLP Consulting: Consulted on automated document analysis and risk assessment for the European Central Bank, leveraging NLP technologies.
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+ - Aerospace Anomaly Detection: Developed a PoC for Aerospace manufacturing, using generative diffusion models to create synthetic data for training anomaly detection models.
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+ - Retail Automation: Applied Vision and Skeletal Tracking for supermarket automation, modernizing retail operations.
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+ - Public Speaking and Training: Regularly presented talks and training sessions on topics such as KI-Transfer Plus for the Bayerischen Staatsministeriums für Digitales, and KI in Biotech for the BioEntrepreneurship Summit, spreading AI knowledge and fostering digital transformation in the Health/Pharma sector..
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+
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+
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+ #### PROJECT LEAD - INNOVATIVE TECHNOLOGIES
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+ #### Nanotemper Technologies GmbH | Munich | 5/2016 - 3/2019
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+
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+ Project Lead in the Future Technologies Department, Scientist Bioanalytics and all-rounder in bioanalytics/data/optoelectronics. Contributions and successes:
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+ - Created and applied Deep Learning models for interpreting biophysical data for pharmaceutical stability in antibody development
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+ - Designed, built, and programmed prototype optoelectronic apparatus for the rapid analysis of biosimilar pharmaceutical molecules
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+ - Introduced FPGA technology for high-speed data collection and analysis, now used in the key products at Nanotemper
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+
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+ #### RESEARCH SCIENTIST
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+ #### Max Planck Institute Of Neurobiology | Martinsried | 02/2016 - 04/2019
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+
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+ Driven by an interest in Biotech, I found a role in research working on biosensors, particularly on optical probes of neural activity (Optogenetics). Contribution and success:
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+ - Designed, built and utilized a robotic screening platform for the high-throughput engineering of biosensors.
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+ - Utilised image-processing and machine-learning techniques to collect and analyse biosensor data.
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+ - Automated the development of large molecules by FACS-based directed protein evolution.
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+ - Patented new CRISPR/Cas9 technology for high-throughput protein engineering.
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+
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+ #### CONSULTANT FOR THE NETFLIX SERIES 'BIOHACKERS'
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+ #### Netflix | Munich | 01/2019 - 12/2019
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+
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+ In this role, I advised on the scientific concepts, storylines and film set for this popular Netflix series. Contribution and success:
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+ - Helped design and build the Laboratory and ‘Biohacking’ labs
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+ - Modified the scripts to keep scientific accuracy
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+ - Location scouting and liaison with the LMU to organise research labs for filming
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+
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+ #### Doctoral Candidate
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+ #### Max Planck Institute for Biochemistry
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+
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+ My PhD thesis was all about Optical brain-computer interfaces, and synthesizing molecular sensors for optically imaging brain activity. I devised a new biomolecular targeting technique and developed compounds for high-speed optical analysis of neuron activity.
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+ - Molecular Sensor Development: Designed, synthesized, and tested molecular sensors to optically image brain activity, advancing neuroimaging capabilities.
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+ - Biomolecular Targeting Technique: Developed a novel technique for labelling live cells with organic dye, utilizing pro-drug techniques used in pharmaceutical development, enhancing the precision of cell tracking and analysis.
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+ - Neuronal Activity Analysis: Designed a high-speed optical analysis setup for cultured neurons and developed specialized compounds for this purpose, improving our understanding of neuron activity.
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+
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+ ## SKILLS
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+ - Strong interest in customer experience and Machine Learning transformations (e.g. expectation management, stakeholder alignment, team reorganization etc.)
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+ - Ability to work autonomously in the completion of deliverables
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+ - Ability to provide technical and analytic direction, guidance and roadmaps for ML projects
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+ - Excellent communication and presentation skills: able to explain Analytics in non-technical terms to business users (C-level, investors, public presentations etc.)
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+ - Deep technical expertise and strong problem-solving and data-analysis skills
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+
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+
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+
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+ ## AWARDS
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+
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+ #### The United Nations COVID-19 Detect & Protect Challenge
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+ - The United Nations Development Programme Centre for Technology, Innovation and Sustainable Development · Aug 2020
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+
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+ #### AI at the Edge Challenge with NVIDIA - Artificial Intelligence of Things (AIoT)
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+ - Issued by Nvidia · Mar 2020
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+
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+ #### Create Intelligence at the Edge - Artificial Intelligence on FPGA
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+ - Avnet and Xilinx · Dec 2018
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+
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+ #### PATENTS
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+ - WO2018020050A1 - Targeted in situ protein diversification by site-directed DNA cleavage and repair
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+
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+
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+ ## EDUCATION
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+
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+ #### PhD in Organic Chemistry
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+ - Max Planck Institute of Biochemistry
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+
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+ #### Honours Degree - Biochemistry
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+ - Monash University Melbourne
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+
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+ #### Bachelor of Science - Double Major -
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+ - Chemistry / Molecular Biology
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+ - University of Tasmania
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+
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+ #### Nanodegree - Deep Reinforcement Learning
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+ - Udacity Online
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+
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+ #### Nanodegree - Deep Learning
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+ - Udacity Online
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+
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+
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+ ___________________________________
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+ 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 🚀
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+
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+ #### Reach out via [LinkedIn](https://www.linkedin.com/in/dnhkng)
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+ url: https://huggingface.co/dnhkng/RYS-XLarge
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+ branch: main
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+ download date: 2024-08-07 03:20:52
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