The workshop will focus on the open-source ecosystem that is helping make progress in the modern machine learning development. Large Language Models will be an important part of the workshop since they are everywhere now. However, it will not be limited to LLMs.
We will also cover many concepts (e.g. quantization, distributed training etc.) underlying the tools. We will be using all these tools to work on various use-cases: Retrieval Augmented Generation (RAG) Systems, making large language models small enough to be usable in your local machines, deploying the models, among others.
Some of the tools we will be looking into are: Huggingface, open-source models like Llama family, Phi3 family etc., python modules like streamlit, transformers etc., vector databases like ChromaDB, frameworks like Llama-index, model hosting services like together ai among many others. We will also go into nuances of what "open-source" even means in the age of LLMs.
You do not need to know any machine learning but the workshop will assume that you are able to code (hopefully in python). You must bring your machines to the workshop. We will send instructions before the workshop for the setup required before attending the workshop.
Please bring you Laptops to the workshop. The workshop will be in
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The workshop will focus on the open-source ecosystem that is helping make progress in the modern machine learning development. Large Language Models will be an important part of the workshop since they are everywhere now. However, it will not be limited to LLMs.
We will also cover many concepts (e.g. quantization, distributed training etc.) underlying the tools. We will be using all these tools to work on various use-cases: Retrieval Augmented Generation (RAG) Systems, making large language models small enough to be usable in your local machines, deploying the models, among others.
Some of the tools we will be looking into are: Huggingface, open-source models like Llama family, Phi3 family etc., python modules like streamlit, transformers etc., vector databases like ChromaDB, frameworks like Llama-index, model hosting services like together ai among many others. We will also go into nuances of what "open-source" even means in the age of LLMs.
You do not need to know any machine learning but the workshop will assume that you are able to code (hopefully in python). You must bring your machines to the workshop. We will send instructions before the workshop for the setup required before attending the workshop.
Please bring you Laptops to the workshop. The workshop will be in English.
Siddhartha Singh
Siddhartha Singh is a machine learning researcher at the NLP group (under Marcel Gygli) at Berner Fachhochschule. He works extensively on RAG Systems, training new Large Language models and designing/engineering machine learning systems.
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