Looking for an expert in modern LLMs? I've got the experience you need. I'll guide you through every step, fine-tuning everything from data collection to model training and improvement.
Why me? Well, with six years of experience in deep learning R&D projects, I've mastered a range of roles - from leading a team to rolling up my sleeves as an engineer. I've built and improved products from scratch and I'm keen to do the same for you.
Worried about your team? Don't be. With four years as a lecturer at Russia’s best university, I can equip them with the skills they need to succeed.
Want to know more? Check out my CV and LinkedIn for the full scoop.
Currently, I am open for a new opportunities.
@BobaZooba | CV | LinkedIn | [email protected]
Cutting Edge & Easy LLM Finetuning using the most advanced methods (QLoRA, DeepSpeed, GPTQ, Flash Attention 2, FSDP, etc)
Are you using Large Language Models (LLMs) for your work and want to train them more efficiently with advanced methods? Wish to focus on the data and improvements rather than repetitive and time-consuming coding for LLM training?
X—LLM is your solution. It's a user-friendly library that streamlines training optimization, so you can focus on enhancing your models and data. Equipped with cutting-edge training techniques, X—LLM is engineered for efficiency by engineers who understand your needs.
X—LLM is ideal whether you're gearing up for production or need a fast prototyping tool.
Tale Quest
is my personal project which was built using xllm
and Shurale
. It's an interactive text-based game
in Telegram
with dynamic AI characters, offering infinite scenarios
You will get into exciting journeys and complete fascinating quests. Chat
with George Orwell
, Tech Entrepreneur
, Young Wizard
, Noir Detective
, Femme Fatale
and many more
Try it now: https://t.me/talequestbot
Practice English with your personal AI native speaker. Exciting text & voice communication 24/7 with a most advanced AI
15,000+ happy users
Try it now: https://t.me/papayaaibot
HuggingFace Hub | 7B | 7B-GPTQ |
---|---|---|
Shurale-v1 | Link | Link |
As a seasoned professional with over six years in Conversational AI, Deep Learning and Natural Language Processing, I excel in roles as a Machine Learning Engineer, Research Engineer, Team Lead and Mentor.
I am intrigued by the potential of Large Language Models (LLMs) and looking for opportunities to utilise my talents in this area. Although I'm based in Georgia, I am globally mobile and prepared for remote work arrangements.
My achievements:
- Repeatedly achieved significant success in product development: increased customer satisfaction rates in open domain dialog system (from 20% to 75%), reduced translation costs for various B2B clients (from 15% to 45%), and improved machine translation quality (by up to 50%).
- Developed an open-domain dialog system that outperformed competitors under significantly limited resources, which was integrated into VK, reaching 86% of Russian users (101.7 million).
- Built various projects from scratch: machine translation quality estimation, automatic error correction in translation, 4 open domain and goal-oriented dialog assistants.
- Managed a total of 15 people in different companies (the largest team is 4 people).
- Trained, distil and deployed in production LLMs (7B, 13B, 30B) using novel approaches such as LoRA.
- Conducted a course that had been awarded for 4 consecutive years and graduated 4 cohorts of students (more than 80 people). Many of the students work in positions like Team Lead, Senior, PhD, Middle in leading technology companies and universities in Russia and beyond.
- Led and actively participated in student research. Master thesis projects: LLM Dialog Model Capable of Understanding and Sending Images (2023); Semantic Model Distillation (2020); Using Memory in Dialog Models (2023); Augmentation Methods NN Models (2020); Multi-domain Sentence Embeddings (2020).
- Pioneered the development of one of the first banking chatbots in Russia.
- Accomplished in developing solutions using the GPT-family API, including dataset generation using advanced methods.
Tools: Python, PyTorch, transformers, Docker, FastAPI, GCP, LLMs, ONNX, Triton Inference Server, unit tests, Git, MongoDB, Redis, Celery, Amplitude, Github Actions, Circle CI, Sentry, codecov, mypy, black, pre-commit hooks, faiss, Notion, Agile, Scrum, prompt engineering, CoT, data labeling and collecting using LLMs.