hands-on-llms
doc_chat_api
hands-on-llms | doc_chat_api | |
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1 | 1 | |
2,329 | 7 | |
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8.7 | 2.7 | |
about 1 month ago | 10 months ago | |
Jupyter Notebook | Python | |
MIT License | - |
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hands-on-llms
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Where to start
There are 3 courses that I usually recommend to folks looking to get into MLE/MLOps that already have a technical background. The first is a higher-level look at the MLOps processes, common challenges and solutions, and other important project considerations. It's one of Andrew Ng's courses from Deep Learning AI but you can audit it for free if you don't need the certificate: - Machine Learning in Production For a more hands-on, in-depth tutorial, I'd recommend this course from NYU (free on GitHub), including slides, scripts, full-code homework: - Machine Learning Systems And the title basically says it all, but this is also a really good one: - Hands-on Train and Deploy ML Pau Labarta, who made that last course, actually has a series of good (free) hands-on courses on GitHub. If you're interested in getting started with LLMs (since every company in the world seems to be clamoring for them right now), this course just came out from Pau and Paul Iusztin: - Hands-on LLMs For LLMs I also like this DLAI course (that includes Prompt Engineering too): - Generative AI with LLMs It can also be helpful to start learning how to use MLOps tools and platforms. I'll suggest Comet because I work there and am most familiar with it (and also because it's a great tool). Cloud and DevOps skills are also helpful. Make sure you're comfortable with git. Make sure you're learning how to actually deploy your projects. Good luck! :)
doc_chat_api
What are some alternatives?
MLSys-NYU-2022 - Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022
SearchWithOpenAI - Quick start. Index multiple documents in a repository using HuggingFace embeddings. Save them in Chroma and / or FAISS for recall. Choose OpenAI or Azure OpenAI APIs to get answers to your questions - Q&A with OpenAI and Azure OpenAI.
finetuned-qlora-falcon7b-medical - Finetuning of Falcon-7B LLM using QLoRA on Mental Health Conversational Dataset
repochat - Chatbot assistant enabling GitHub repository interaction using LLMs with Retrieval Augmented Generation
AutoGPTQ - An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.
git-agent - Langchain Agent utilizing OpenAI Function Calls to execute Git commands using Natural Language
LLM-Finetuning-Hub - Toolkit for fine-tuning, ablating and unit-testing open-source LLMs. [Moved to: https://github.com/georgian-io/LLM-Finetuning-Toolkit]
llm-client-sdk - SDK for using LLM
Local-LLM-Langchain - Load local LLMs effortlessly in a Jupyter notebook for testing purposes alongside Langchain or other agents. Contains Oobagooga and KoboldAI versions of the langchain notebooks with examples.
CASALIOY - ♾️ toolkit for air-gapped LLMs on consumer-grade hardware