Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality. Learn more →
Top 23 Jupyter Notebook large-language-model Projects
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
DeepLearningExamples
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
-
FinGPT
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
-
Promptify
Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research
-
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
-
alpaca_eval
An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.
-
Get-Things-Done-with-Prompt-Engineering-and-LangChain
LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis.
-
-
-
fromage
🧀 Code and models for the ICML 2023 paper "Grounding Language Models to Images for Multimodal Inputs and Outputs".
-
PIXIU
This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI).
-
-
KG_RAG
Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks
-
-
ToolQA
ToolQA, a new dataset to evaluate the capabilities of LLMs in answering challenging questions with external tools. It offers two levels (easy/hard) across eight real-life scenarios.
-
augmented-interpretable-models
Interpretable and efficient predictors using pre-trained language models. Scikit-learn compatible.
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Project mention: Ask HN: People who switched from GPT to their own models. How was it? | news.ycombinator.com | 2024-02-26This is a very nice resource: https://github.com/mlabonne/llm-course
Project mention: Finetuning an LLM-Based Spam Classifier with LoRA from Scratch | news.ycombinator.com | 2024-05-11
Project mention: GPT-4, without specialized training, beat a GPT-3.5 class model that cost $10B | news.ycombinator.com | 2024-03-24There is also the open source FinGPT, that is claimed to beat GPT4 in some benchmarks at a fine tuning cost of $17.25.
https://github.com/AI4Finance-Foundation/FinGPT
Project mention: Promptify 2.0: More Structured, More Powerful LLMs with Prompt-Optimization, Prompt-Engineering, and Structured Json Parsing with GPT-n Models! 🚀 | /r/ArtificialInteligence | 2023-07-31First up, a huge Thank You for making Promptify a hit with over 2.3k+ stars on Github ! 🌟
Project mention: ChatGPT provides false information about people, and OpenAI can't correct it | news.ycombinator.com | 2024-04-29> The article talks about OpenAI being unwilling to correct errors. But they just can’t.
There are actually several algorithms intended to allow fact editing in LLMs: https://github.com/zjunlp/EasyEdit?tab=readme-ov-file#curren...
They don't work perfectly (e.g. "Tim Cook is CEO of Apple" and "The CEO of Apple is Tim Cook" for some reason have to be edited separately) but there are certainly techniques available.
Alpaca Eval is open source and was developed by the same team who trained the alpaca model afaik. It is not like what you said in the other comment
Project mention: Get-Things-Done-with-Prompt-Engineering-and-LangChain: NEW Data - star count:617.0 | /r/algoprojects | 2023-12-10
Project mention: GPT-based ontological extraction tools, including SPIRES | news.ycombinator.com | 2023-07-24
Project mention: Show HN: Hacker Search – A semantic search engine for Hacker News | news.ycombinator.com | 2024-05-02HyDE apparently means “Hypothetical Document Embeddings”, which seems to be a kind of generative query expansion/pre-processing
https://arxiv.org/abs/2212.10496
https://github.com/texttron/hyde
From the abstract:
Given a query, HyDE first zero-shot instructs an instruction-following language model (e.g. InstructGPT) to generate a hypothetical document. The document captures relevance patterns but is unreal and may contain false details. Then, an unsupervised contrastively learned encoder~(e.g. Contriever) encodes the document into an embedding vector. This vector identifies a neighborhood in the corpus embedding space, where similar real documents are retrieved based on vector similarity. This second step ground the generated document to the actual corpus, with the encoder's dense bottleneck filtering out the incorrect details.
Project mention: A list of system prompts used for biomedical RAG (KG-RAG) using LLM | news.ycombinator.com | 2024-01-10
Project mention: Gemini is only 1x Chinchilla, so it undertrained for production | /r/singularity | 2023-12-071x chinchilla means it's not really undertrained but that more could be squeezed without excessive difficulty https://arxiv.org/abs/2305.16264
Project mention: 🔍📊 Exciting development in the AI world: Introducing ToolQA, a new dataset that evaluates how well Large Language Models (LLMs) can use external tools for question answering. | /r/machinelearningnews | 2023-07-01
If you refer to React agent, you can check this link
Project mention: A Simple Version of Grok 1.5/ GPT-4 Vision from scratch, in one PyTorch file | news.ycombinator.com | 2024-05-05
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Jupyter Notebook large-language-models related posts
-
Finetuning an LLM-Based Spam Classifier with LoRA from Scratch
-
A Simple Version of Grok 1.5/ GPT-4 Vision from scratch, in one PyTorch file
-
Finetune a GPT Model for Spam Detection on Your Laptop in Just 5 Minutes
-
ChatGPT provides false information about people, and OpenAI can't correct it
-
Insights from Finetuning LLMs for Classification Tasks
-
Comparing 5 ways to implement Multihead Attention in PyTorch
-
Large Language Model Course
-
A note from our sponsor - InfluxDB
www.influxdata.com | 13 May 2024
Index
What are some of the best open-source large-language-model projects in Jupyter Notebook? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | llm-course | 29,486 |
| 2 | LLMs-from-scratch | 16,129 |
| 3 | DeepLearningExamples | 12,660 |
| 4 | FinGPT | 11,586 |
| 5 | Promptify | 3,046 |
| 6 | ReAct | 1,597 |
| 7 | EasyEdit | 1,412 |
| 8 | alpaca_eval | 1,134 |
| 9 | Get-Things-Done-with-Prompt-Engineering-and-LangChain | 966 |
| 10 | ontogpt | 512 |
| 11 | xmtf | 496 |
| 12 | fromage | 458 |
| 13 | PIXIU | 406 |
| 14 | llm-search | 381 |
| 15 | hyde | 362 |
| 16 | KG_RAG | 340 |
| 17 | datablations | 295 |
| 18 | ToolQA | 210 |
| 19 | langforge | 163 |
| 20 | localLLM_guidance | 147 |
| 21 | FastLoRAChat | 119 |
| 22 | seemore | 58 |
| 23 | augmented-interpretable-models | 37 |
Sponsored
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com