Red Pajama - Operation: Freeing LLaMA
Key Takeaways
The RedPajama project creates LLaMA models from scratch, avoiding licensing issues with Meta AI's LLaMA models, utilizing datasets like RedPajama-Data-1T on Hugging Face.
Full Transcript
alright so this video is going to be a quick one I just wanted to talk about this project called red pajam so this is from the group called together computer I think is also their name and this is basically the start of a whole project to reproduce a fully open source version of the Llama models and they've kicked it off by first releasing the data set so it's pretty impressive their plan is to basically create a a set of open models of the Llama models and to do that they actually have to train the foundation models on over a trillion tokens so here's the data set based on what the original llama actually used so this is over a trillion tokens they're saying it's 1.2 trillion tokens if we remember back llama the 7 billion and the 13 billion parameter models were trained on one trillion tokens and the two bigger models going up to the 65 billion parameter model was trained on 1.4 trillion tokens so while it might seem perhaps not a big deal that oh they've released this data set because it's just scraped from the internet it is definitely a big deal in regards to the pre-processing and all the things that have been done for that so they've managed to put that all together in a way that can actually go through and make a nice cleaned high quality data set on par with what llama was trained on now in theory that should mean that we can get a model out that will be as good as llama and so they point out in here that basically this has been uh sort of a takeoff moment for AI and certainly for large language models that these open source models have come along but unfortunately a lot of the models like llama alpaca vicuna koala are not really fully open there are some that like pythia open chat kit open assistant and Dolly which are fully open but a lot of the others are not so this is a way of them kicking it off and getting started to make fully open Llama model so the group there's quite a number of groups together about this we've got together themselves there's also people from Stanford from eth in Switzerland from Mila in Canada it's definitely a big International effort to make this thing happen and so they talk about the three main components of this being the pre-training data which needs to be both high quality and have broad coverage the that's what they were releasing now the base models which is apparently their training at the moment and then third will be the instruction tuning data sets which we'll probably see a variety of those come out over then so anyway they go on a little bit about the different reasons why and some things about llama in there and then they break down the actual data set so the data set is made of five dumps of common crawl which is basically looking just scraping the internet of pages and then they've got a number of different filters that they're using to clean that they've got the C4 standard C4 data set which came out of the T5 model back in 2019 they've got GitHub they've got archive papers they've got the Books Corpus which I'm pretty sure was used in the original GPT 2 model Wikipedia been used in many models and stack exchange there as well so this is quite impressive the number of tokens that they've got here that are putting all together to create something that's sort of 1.2 trillion tokens this is definitely in the ballpark of what where llama was so they put this up on hugging face if you wanted to go and train your own llama model now and you had the money and the compute you would certainly be able to do that the data set is on hanging face it's a trillion tokens it will take you probably quite a long time to download it and they've also got in here a smaller version of this which is the sample data set so this one you can actually go through and have a look at it this is only a billion tokens a subset from the main one so anyway just the main thing to sort of keep you informed here is that we've got a full open source llama model that sounds like it's well on the way to coming out which will mean that a lot of things that people were doing with fukuna with koala with a lot of these models there's probably going to be versions of these that are going to be fully open source in the not too distant future anyway on that note as always if you've got questions please put them in the comments if you found this useful please click like And subscribe I will see you in the next video
Original Description
Blog Post: https://www.together.xyz/blog/redpajama
Dataset: https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T
In this video, we look at the RedPajama project by Together which is working on creating a set of LLaMA models from scratch that won't have any of the licensing problems with using the LLaMA models for Meta AI
For more tutorials on using LLMs and building Agents, check out my Patreon:
Patreon: https://www.patreon.com/SamWitteveen
Twitter: https://twitter.com/Sam_Witteveen
My Links:
Linkedin: https://www.linkedin.com/in/samwitteveen/
Github:
https://github.com/samwit/langchain-tutorials
https://github.com/samwit/llm-tutorials
Watch on YouTube ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
Playlist
Uploads from Sam Witteveen · Sam Witteveen · 38 of 60
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
▶
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
LangChain Basics Tutorial #1 - LLMs & PromptTemplates with Colab
Sam Witteveen
LangChain Basics Tutorial #2 Tools and Chains
Sam Witteveen
ChatGPT API Announcement & Code Walkthrough with LangChain
Sam Witteveen
Trying Out Flan 20B with UL2 - Working in Colab with 8Bit Inference
Sam Witteveen
LangChain - Conversations with Memory (explanation & code walkthrough)
Sam Witteveen
LangChain Chat with Flan20B
Sam Witteveen
LangChain - Using Hugging Face Models locally (code walkthrough)
Sam Witteveen
PAL : Program-aided Language Models with LangChain code
Sam Witteveen
Building a Summarization System with LangChain and GPT-3 - Part 1
Sam Witteveen
Building a Summarization System with LangChain and GPT-3 - Part 2
Sam Witteveen
Microsoft's Visual ChatGPT using LangChain
Sam Witteveen
Building a Summarization System with LangChain - Part 3 Using ChatGPT Turbo
Sam Witteveen
LangChain Agents - Joining Tools and Chains with Decisions
Sam Witteveen
Investigating Alpaca 7B - Finetuned LLaMa LLM
Sam Witteveen
Comparing LLMs with LangChain
Sam Witteveen
Running Alpaca7B in Colab
Sam Witteveen
How to finetune your own Alpaca 7B
Sam Witteveen
How to make a custom dataset like Alpaca7B
Sam Witteveen
Understanding Constitutional AI - the paper and key concepts
Sam Witteveen
Using Constitutional AI in LangChain
Sam Witteveen
Talking to Alpaca with LangChain - Creating an Alpaca Chatbot
Sam Witteveen
Text-to-video-synthesis with Diffusers and Colab
Sam Witteveen
Meet Dolly the new Alpaca model
Sam Witteveen
Checking out the Cerebras-GPT family of models
Sam Witteveen
A Step-by-Step Guide to Fine-Tuning Your Dolly Model (tutorial)
Sam Witteveen
Is GPT4All your new personal ChatGPT?
Sam Witteveen
Raven - RWKV-7B RNN's LLM Strikes Back
Sam Witteveen
Talk to your CSV & Excel with LangChain
Sam Witteveen
Vicuna - 90% of ChatGPT quality by using a new dataset?
Sam Witteveen
Koala Revealed: The ChatGPT Alternative You Need to Know! 🔍
Sam Witteveen
Running Koala for free in Colab. Your own personal ChatGPT? (tutorial)
Sam Witteveen
BabyAGI: Discover the Power of Task-Driven Autonomous Agents!
Sam Witteveen
Auto-GPT - How to Automate a Task Based AI with GPT-4
Sam Witteveen
Improve your BabyAGI with LangChain
Sam Witteveen
Generative Agents - Deep Dive and GPT-4 Recreation
Sam Witteveen
GPT4ALLv2: The Improvements and Drawbacks You Need to Know!
Sam Witteveen
Dolly 2.0 by Databricks: Open for Business but is it Ready to Impress!
Sam Witteveen
Red Pajama - Operation: Freeing LLaMA
Sam Witteveen
Investigating Open Assistant - Models, Datasets and Addons
Sam Witteveen
Investigating MiniGPT-4 - The Secret behind GPT-V?
Sam Witteveen
Stable LM 3B - The new tiny kid on the block.
Sam Witteveen
Bard can now code and put that code in Colab for you.
Sam Witteveen
Checking out Bark: a Text to Speech system by Suno AI
Sam Witteveen
Fine-tuning LLMs with PEFT and LoRA
Sam Witteveen
Master PDF Chat with LangChain - Your essential guide to queries on documents
Sam Witteveen
Using LangChain with DuckDuckGO Wikipedia & PythonREPL Tools
Sam Witteveen
Building Custom Tools and Agents with LangChain (gpt-3.5-turbo)
Sam Witteveen
StableVicuna: The New King of Open ChatGPTs?
Sam Witteveen
WizardLM: Evolving Instruction Datasets to Create a Better Model
Sam Witteveen
LaMini-LM - Mini Models Maxi Data!
Sam Witteveen
Finding the Best Free ChatGPT
Sam Witteveen
MPT-7B - The First Commercially Usable Fully Trained LLaMA Style Model
Sam Witteveen
LangChain Retrieval QA Over Multiple Files with ChromaDB
Sam Witteveen
LangChain Retrieval QA with Instructor Embeddings & ChromaDB for PDFs
Sam Witteveen
LangChain + Retrieval Local LLMs for Retrieval QA - No OpenAI!!!
Sam Witteveen
Transformers Agent - Is this Hugging Face's LangChain Competitor?
Sam Witteveen
StarCoder - The LLM to make you a coding star?
Sam Witteveen
Testing Starcoder for Reasoning with PAL
Sam Witteveen
The New Wizards - Unfiltered & Unaligned
Sam Witteveen
Camel + LangChain for Synthetic Data & Market Research
Sam Witteveen
More on: LLM Engineering
View skill →Related Reads
📰
📰
📰
📰
How I Stopped Fighting Hallucinations in LLM Data Extraction
Dev.to · zhongqiyue
Anthropic’s Claude Sonnet 5 Is “Near-Opus Intelligence” For All Plans via @sejournal, @martinibuster
Search Engine Journal
Understanding How LLMs Work: From Text to Tokens, Embeddings, Transformers, and Predictions
Dev.to · Klinsmann R
How ChatGPT Understands Your Questions: A Beginner-Friendly Guide
Dev.to · Shreyas Rasaikar
🎓
Tutor Explanation
DeepCamp AI