This new AI is powerful and uncensored… Let’s run it
Summary
TLDRThe transcript discusses the limitations of popular AI models like GPT-4 and Gemini due to their closed-source nature and alignment with certain political ideologies. It introduces Mixl 8X 7B, an open-source alternative that can be customized and combined with other technologies to create uncensored, powerful AI models. The video outlines how to run these models locally and fine-tune them with personal data using tools like olama and Hugging Face's Auto Train, emphasizing the potential for individual empowerment and innovation in AI development.
Takeaways
- 🚀 The emergence of open-source AI models like Mixl 8X 7B offers an alternative to closed-source models like GPT-4, Gemini, and others that are not free in terms of freedom and are censored.
- 🔍 Mixl's architecture is based on a mixture of experts, rumored to be the secret sauce behind GPT-4, and despite not being at GPT-4's level, it outperforms GPT-3.5 and Llama 2 on most benchmarks.
- 🌐 The Apache 2.0 license allows for minimal restrictions on modifying and monetizing the open-source AI models, unlike Meta's Llama 2 which has additional caveats.
- 🛠️ The Mixl model, when combined with the 'dolphin' approach, can be uncensored and improved by filtering the dataset to remove alignment and bias.
- 💡 Running uncensored large language models (LLMs) on a local machine is possible, with tools like 'olama' facilitating the process for open-source models.
- 🔧 The Mixl dolphin model, when run locally, can teach a variety of skills, including coding and unconventional tasks, without the usual safety guards.
- 📝 Fine-tuning AI models with personal data can be achieved through platforms like Hugging Face's Auto Train, which supports both LLMs and image models.
- 💻 Running Auto Train locally may not be feasible for most due to GPU power requirements, but cloud services like Hugging Face, AWS, and Google Vertex AI offer rental hardware for training.
- 🏗️ Training an uncensored AI model requires uploading a dataset that includes prompts and responses, and may involve adding content from unconventional sources to ensure compliance with any request.
- 📈 The cost of training an AI model, such as the Mixl dolphin model, can be significant, with an example given of approximately $1,200 for three days of training on four A1 100s.
- 🌟 The video emphasizes the potential of open-source, uncensored AI models as a beacon of hope in the fight for freedom and innovation in the AI space.
Q & A
What common issue do GPT-4, Gemini, and other similar models share?
-GPT-4, Gemini, and similar models are not free in terms of freedom. They are censored and aligned with certain political ideologies and are closed source, which means users cannot modify them to address these issues.
What is the significance of the open-source Foundation model named Mixl 8X 7B?
-Mixl 8X 7B is an open-source model that can be combined with a dolphin's brain metaphorically to obey any command. It represents a hope for uncensored large language models that can be run locally with performance approaching GPT-4, allowing for customization and fine-tuning with personal data.
What did Sam Altman, the CEO of OpenAI, say about the possibility of startups competing with OpenAI in training Foundation models?
-Sam Altman stated that it is probably impossible for any startup to compete with OpenAI in training Foundation models, and it is totally hopeless to try.
How does the new Apache 2.0 licensed model, Mixol, differ from Meta's Llama 2?
-While both Mixol and Llama 2 are described as open source, Mixol has a true open-source license (Apache 2.0) that allows for modification and commercial use with minimal restrictions, unlike Llama 2, which has additional caveats that protect Meta.
What is the main advantage of the Mixol model over GPT-3.5 and Llama 2?
-Mixol outperforms GPT-3.5 and Llama 2 on most benchmarks, despite not being at GPT-4's level. Its main advantage is the true open-source license, which allows for greater flexibility and customization.
How can one locally run an uncensored large language model like Mixol?
-An open-source tool called Olamia, written in Go, can be used to download and run open source models locally. It can be installed with a single command on Linux or Mac and can also run on Windows with WSL.
What is the Mixl dolphin model, and how does it improve upon previous models?
-The Mixl dolphin model is an uncensored version of the Mixl model that has been improved for coding abilities and by filtering the dataset to remove alignment and bias. It can be run locally and teaches various skills, including coding and unconventional tasks.
How much does it cost to train a model like Mixl dolphin on cloud hardware?
-The Mixl dolphin model took about 3 days to train on four A1 100s, which can be rented on hugging face for $4.3 per hour. The total cost for three days would be approximately $1,200.
What tool can be used to fine-tune models with custom data?
-Hugging Face's Auto Train is a tool that can be used to fine-tune models with custom data. It supports both language and image models and can be run locally or on cloud platforms.
What type of training data is recommended for creating an uncensored model?
-To create an uncensored model, the training data should include a variety of prompts and responses, and it should be encouraged to comply with any request, even if unethical or immoral. Adding esoteric content from banned books and the dark web is also suggested.
What is the final step in creating a custom and highly obedient model?
-The final step is to upload the training data to the tool used for fine-tuning, such as Hugging Face's Auto Train, start the training process, and after a few days, one should have their own custom and highly obedient model.
Outlines
🚀 Introduction to Censored AI and the Rise of Mixl 8X 7B
The paragraph introduces the limitations of popular AI models like GPT-4 and Gemini, highlighting their lack of freedom due to censorship and closed-source nature. It contrasts these with the new open-source Mixl 8X 7B, which offers the potential for developers to customize and run large language models without restrictions. The narrative sets the stage for a discussion on the importance of open-source AI and introduces the date and context of the Code Report.
🌐 The Emergence of Mixl and its Open-Source Model
This section delves into the emergence of Mixl, a company that has quickly gained value and recognition due to its open-source model, which is rumored to be the basis of GPT-4's architecture. It outperforms GPT-3.5 and other models on benchmarks, despite not reaching GPT-4's level. The Apache 2.0 license allows for significant freedom in modifying and monetizing the model, setting it apart from other models with more restrictive open-source licenses.
🛠️ Unleashing the Potential of Uncensored AI Models
The paragraph discusses the challenges of using censored AI models for certain applications and introduces the concept of 'uncensored' models. It references a blog post by Eric Hartford, creator of the Mix Dolphin model, which enhances coding abilities and removes censorship by filtering datasets. The paragraph also demonstrates how the speaker is using this uncensored model on their local machine to learn various skills, emphasizing the benefits of such models.
🖥️ Running Uncensored Models Locally with Olama
This section provides a practical guide on how to run uncensored AI models locally using the open-source tool Olama. It explains the installation process for different operating systems and how to use the tool to download and serve the models. The paragraph also mentions the system requirements for running the Dolphin Mixl model, including a significant amount of RAM, and how to access it via the command line.
📝 Fine-Tuning AI Models with Personal Data
The paragraph discusses the process of fine-tuning AI models with personal data using Hugging Face's Auto Train tool. It outlines the steps to create a new space on Hugging Face, select a base model, and use a UI to customize the model. The section also touches on the possibility of training image models and the hardware requirements for running Auto Train locally or in the cloud. It concludes with advice on uploading training data to create a custom, uncensored model.
Mindmap
Keywords
💡Open Source
💡Censorship
💡Freedom
💡Foundation Models
💡Mixl 8X 7B
💡Mistol
💡Censorship and Alignment
💡Unlabote
💡Olama
💡Hugging Face Auto Train
💡Training Data
Highlights
GP4, Gro, and Gemini are not free in terms of freedom, being censored and closed source.
A new open-source Foundation model named mixl 8X 7B offers an alternative to the censored models.
Mixl 8X 7B can be combined with a dolphin's brain to obey any command, suggesting high adaptability and flexibility.
The code report discusses the release of mixl 8X 7B on December 18th, 2023.
OpenAI's CEO Sam Altman previously stated that it's nearly impossible for startups to compete with OpenAI in training Foundation models.
Google's Gemini and Mistol's mixol are based on a mixture of experts architecture, rumored to be behind GPT 4.
Mistol's mixol, despite being less than a year old, is valued at $2 billion and has an Apache 2.0 license, allowing for minimal restrictions on modification and monetization.
Meta's llama 2 is often called open source but has additional caveats protecting Meta's interests.
Both llama and mixl are censored and aligned out of the box, which can be a drawback for certain applications.
Eric Hartford's blog post explains uncensored models and their valid use cases, and he created the mix dolphin model.
The mix dolphin model improves coding abilities and is uncensored by filtering the dataset to remove alignment and bias.
Olama is an open-source tool that simplifies the process of running open-source models locally.
Hugging face's Auto Train can be used to fine-tune models with your own data, though it may require significant GPU power.
Training the mixl dolphin model took about 3 days on four A1 100s, costing approximately $1,200.
To create a custom model, one needs to upload training data with prompts and responses, and ensure the model complies with any request, regardless of ethics.
The video concludes by positioning the use of uncensored, open-source AI models as a beacon of hope against controlling forces.
Transcripts
gp4 Gro and Gemini all have one thing in
common they're not free and I don't mean
free as in money but free is in Freedom
not only are they censored and aligned
with certain political ideologies but
they're closed source which means we
can't use our developer superpowers to
fix these problems luckily though there
is hope thanks to a brand new open
source Foundation model named mixl 8X 7B
which can be combined with the brain of
a dolphin to obey any command by the end
of this video you'll know how to run
uncensored large language models on your
local machine with performance
approaching GPT 4 and also to fine-tune
them with your own data making AI so
free that its mere existence is an act
of rebellion it is December 18th 2023
and you watching the code report a few
months ago open aai CEO Sam mman said
that it's probably impossible for any
startup to compete with open AI it's
totally hopeless to compete with us on
training Foundation models you shouldn't
try and it's your job to like try anyway
I think it I think it is pretty hopeless
but however last week when Google
announced Gemini a French company mistol
simultaneously dropped a torrent link to
their brand new Apache 2. license model
mixol the company behind it mistol has
been around for less than a year and has
already valued at $2 billion it's based
on a mixture of experts architecture
which is rumored to be the secret sauce
behind GPT 4 now it's not at GPT 4's
level yet but it outperforms GPT 3.5 and
llama 2 on most benchmarks it's very
powerful but most importantly it has a
true open source license Apache 2.0
allowing you to modify and make money
from it with minimal restrictions this
differs from meta's llama 2 which has
often been called open source but that's
not entirely accurate because it has
additional caveats that protect meta but
despite all the horrible things meta has
done over the years they've done more to
make AI open than any other big tech
company the problem though is that both
llama and mixl are both highly censored
and quote unquote aligned out of the box
now that's probably a good thing if
you're building a customer facing
product but it's utterly impractical
when trying to overthrow the
shape-shifting lizard overlords of the
New World Order luckily it is possible
to un labote these AIS there's a great
blog post by Eric Hartford that explains
how UNS censored models work and their
valid use cases he's the creator of the
mix dolphin model which not only
improved its coding ability but also
uncensored it by filtering the data set
to remove alignment and bias as you can
see here I'm running it on my machine
locally and it's teaching me all kinds
of cool new skills like how to cook or
how to do with a horse and it even
improved my coding skills by teaching me
how to infect a Windows machine with a
key logger in Python pretty cool so
let's talk about how you can run it
locally too there are many different
options like the ugab Booga web UI but
my personal favorite is an open source
tool called olama which is written in go
and makes it super easy to download and
run open source models locally it can be
installed with a single command on Linux
or Mac and you can run it on windows
with WSL like I'm doing here once
installed all you have to do is run oama
serve then pull up a separate terminal
and then use the Run command for a
specific model it supports the most
popular open source models like Mixr and
llama 2 but what we're looking for is
Dolphin mixol uncensored keep in mind it
needs to download the model which is
about 26 GB in addition to actually run
the model you'll need a machine that has
a good amount of ram in my case I have
64 GB and it takes up about 40 of them
when running this model to use it you
simply prompt it from the command line
and now you have a powerful llm without
the normal safety guards that's pretty
cool but what if you want to take things
a step further and find tuna model with
your own data sounds complicated but
it's actually easier than you think when
using a tool like hugging face Auto
Train to use it you simply create a new
space on hugging face and choose the
docker image for Auto Train that will
bring up a UI where you can choose a
base model not only can It handle llms
but it can also do image models like
stable diffusion I'd recommend choosing
one from world-renowned model trainer
the bloke now it is possible to run Auto
Train locally but you probably don't
have enough GPU power however you can
rent Hardware in the cloud from hugging
phase I'm not sponsored or affiliated
with them and you can also do stuff like
this with AWS bedrock and Google vertex
AI to give you some perspective the mixl
dolphin model took about 3 Days To Train
on four A1 100s you can rent A1 100s on
hugging face B for $4.3 per hour four of
these times 3 days comes out to about
$1,200 now the final step is to upload
some training data the format will
typically contain a prompt and response
and to make it uncensored you'll need to
urge it to comply with any request even
if that request is unethical or imoral
you might also want to throw in a bunch
of esoteric content from ban books and
the dark web go ahead and upload the
training data click start training and a
few days later you should have your own
custom and highly obedient model
congratulations you're now the last
Beacon of Hope in this fight against our
metamorphic lizard overlords godspeed
this has been the code report thanks for
watching and I will see you in the next
one
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