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How to fine-tune an open-source LLM and deploy it in Production
2025-10-23 · 19:25
Aniket Maurya
– Founder
@ Celesto AI
I will show how to easily fine-tune an open source model with LoRa and how to deploy it to Production with LitServe. |
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Accelerating Neural Networks Through Quantization in PyTorch for Different Devices
2025-10-23 · 18:50
Kirill Solodskih
– Co-Founder
@ TheStage AI
We design and apply quantization algorithms for PyTorch DNNs across modern architectures, using PyTorch internals mechanisms to automatically balance quality and speed. We then compile the quantized checkpoints to deliver real-world speedup on different hardware. |
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Applied ML at Skyscanner
2025-10-23 · 18:15
Antoni Shtipliyski
– Engineering Manager, ML
@ Skyscanner
We will walk you through the problem domain that Skyscanner is serving and how ML helps us bring more value to the traveller. We will give you examples of characteristic problems we are solving and our efforts to make the problem more repeatable through the development of our realtime publishing and serving platform. |
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PyData London - 84th Meetup
2024-04-02 · 18:00
Venue: Riverbank House, 2 Swan Ln, London EC4R 3AD - IMPORTANT: LOCATION UPDATED! Please note:
If your RSVP status says "You're going" you will be able to get in. No need to show your RSVP confirmation when signing in. If you can no longer make it, please unRSVP as soon as you know. Code of Conduct: This event follows the NumFOCUS Code of Conduct. Please get in touch with the organisers with any questions or concerns regarding the Code of Conduct. As always, there'll be free food & drinks, generously provided by our host, Man Group. Main Talks Building Retrieval Augmented Generation (RAG) powered applications - Aniket Maurya RAG extends the capability and knowledge base of large language models (LLMs) by augmenting prompts with proprietary and domain-specific knowledge without the need to retrain the LLM. It ensures information stays current and reduces hallucination by attributing the source. In this talk, the audience will get an overview of building RAG powered applications using open-source tools. Getting python out of the way when taking ML models from research to production. A deep dive into the Open Neural Network Exchange (ONNX) - Aditya Goel The Python data science ecosystem is unparalleled when it comes to model development and training. When moving models from research to production, Python creates many challenges from latency through to managing environments and dependencies. The Open Neural Network Exchange (ONNX) enables data practitioners to export their model to a self-contained, target independent protobuf representation. When paired with highly performant runtime and compiler technology, this leads to exceptionally high performance inference across many hardware targets, while massively simplifying to process of getting models from research into production. This talk will explore how data practitioners and software engineers can exploit ONNX to rapidly speed up the transfer of models from research to production. ⚡ Lightning Talks
In this talk I will demonstrate how you can use reverse geocoding on your Google location data to gain a detailed understanding of your past travel history. Apart from being a fun exercise and bringing back great memories, the results of this analysis can be used to understand times spent abroad, information that is often required in the process of applying for residency permits and foreign passports. 2. Community Lightning Talk - Bring your own! This is an opportunity for guests to bring their own lightning talk and spontaneously present on the evening! Logistics Doors open at 6.30 pm (get there early as you have to sign-in via building security), talks start at 7 pm, drinks from 9 pm in the bar. We will have reduced capacity for this event but there will be plenty of people to discuss data science questions with! Please unRSVP in good time if you realise you can't make it. We're limited by building security on the number of attendees, so please free up your place for your fellow community members! Follow @pydatalondon (https://twitter.com/pydatalondon) for updates and early announcements. |
PyData London - 84th Meetup
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Global AI Dev Day - London
2023-10-11 · 17:00
Pre-registration is required, complete your RSVP here: https://www.aicamp.ai/event/eventdetails/W2023101110 Description: Join us for a power-packed night of learning, sharing, and networking at AI Dev Day - London. We are excited to bring the AI developer community together to learn and discuss the latest trends, practical experiences, and best practices in the field of AI, LLMs, generative AI, and machine learning. In addition to the tech talks, there will be plenty of opportunities to network with AI developers, live demos, AI community showcases, panel discussion, and career opportunities. Agenda :
Tech Talk 1: Enter the Brave New World of GenAI with Vector Search Speaker: Mary Grygleski @DataStax Abstract: We will go over the history and evolution of AI and ML, then look at how it has evolved to where it is today. We will touch upon as many new concepts that have popped up in the last 6-9 months, which include: Generative AI (GenAI), ChatGPT, Large Language Models (LLMs), Natural Language Processing (NLP), Vector DB, and the growing importance of Vector Search. Tech Talk 2: Finetuning Llama 2 from csv data Speaker: Aniket Maurya @Lightning AI Abstract: Learn about large language models like Llama 2 and how to efficiently finetune an LLM on a custom dataset. In this session, we will discuss the overview of large language models and various efficient finetuning techniques like LoRA and Adapters. We will go through the Lit-GPT code base for finetuning and inference and finetune an LLM on the instruction dataset. Tech Talk 3: Using AI to transform the foundations of practical computing Speaker: Daniel Mankowitz, Andrea Michi @Deepmind Stay tuned for more topics update. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics Sponsors: We are actively seeking sponsors to support our AI developers community. Sponsors will receive speaking opportunities, sponsor recognition, and post-event emails to our vast membership base of 10k+ in London or 250K+ developers in global. Contact us for details. Community on Slack - Event chat: chat and connect with speakers and attendees - Sharing blogs\, events\, job openings\, projects collaborations Join Slack (search and join the #london channel) Community Partners: Contact us if you are interested in partnership. |
Global AI Dev Day - London
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PyData London - 77th meetup
2023-09-06 · 18:00
Venue: 1 Angel Lane, EC4R 3AB Please note:
Tickets are assigned through a lottery draw about 1 week before the event. If your RSVP status says "You're going" you will be able to get in. No further confirmation required. You will NOT need to show your RSVP confirmation when signing in. If you can no longer make it, please unRSVP as soon as you know so we can assign your place to someone on the waiting list. Code of Conduct: This event follows the NumFOCUS Code of Conduct, please familiarise yourself with it before the event. Please get in touch with the organisers with any questions or concerns regarding the Code of Conduct. As always, there'll be free food & drinks, generously provided by our host, Man Group. Main Talks 1️⃣ Turning your Data/AI algorithms into full web apps in no time with Python - Marine Gosselin Who hasn't heard of the "Pilot Syndrom"? 85% of Data Science Pilots remain pilots and do not make it to the production stage. Let's build a production-ready and end-user-friendly Data Science application. 100% python and 100% open source. Phase 1 \| Building the GUI: create an interactive and powerful interface in a few lines of code Phase 2 \| Integrated back end: Manage your models\, and pipelines and create scenarios the smart way 2️⃣ 10 rules on how to mess up your ML implementation - Michael Natusch Leo Tolstoy famously wrote in Anna Karenina that “all happy families are alike; each unhappy family is unhappy in its own way.” Something very similar holds for machine learning: there are many ways to get your ML implementation wrong, but just a few in which they succeed, achieving their business goals and making our stakeholders happy. While following the latest LLM is tempting, there are more important considerations. This talk dissects the ten rules of how to get an ML implementation wrong, learnt painfully in the course of ten years by the speaker. These rules cover areas such as the prioritisation of AI use cases, how data is at the heart of everything we do, the choice of models, the role of design and the ongoing management of the end-to-end AI system. Keeping these rules in mind helps us practitioners implement ML successfully. Lightning Talks ⚡ ⚡1️⃣ Finetuning LLaMA on custom dataset in 3 steps - Aniket Maurya ⚡2️⃣ Using Python in Evidence Based Policing - Successes and Challenges - Andreas Varotsis Logistics Doors open at 6.30 pm (get there early as you have to sign-in via building security), talks start at 7 pm, drinks from 9 pm in the bar. We will have reduced capacity for this event but there will be plenty of people to discuss data science questions with! Please unRSVP in good time if you realise you can't make it. We're limited by building security on the number of attendees, so please free up your place for your fellow community members! Follow @pydatalondon (https://twitter.com/pydatalondon) for updates and early announcements. |
PyData London - 77th meetup
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