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Brand guidelines

appName: OpenAI

appCategory: Productivity

appTagline: An AI research and deployment company

companyHqRegion: US & Canada

companyStage: Growth Stage

platform: web

pageType: Marketing

hotspotType: Click

pagePatterns:
Landing Page
Footer Section

hotspotType: Scroll Vertically

screenElements:
Thumbnail
Grid List
Button

pagePatterns:
Press & Media Page
Landing Page
Footer Section
Press & Media Page

pageType: Marketing Marketing Marketing

allAppCategories:
Artificial Intelligence
Productivity

screenKeywords:
Powered by @ OpenAl Powered by @ OpenAl
Outlined badge on dark (preferred) Outlined badge on light (preferred)
Powered by @ OpenAl Powered by @ OpenAl
Filled badge on dark Filled badge on light
Download badges
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|T~
Our research ChatGPT Safety overview Company Terms & policies
Overview For Everyone Safety overview About us Terms of use
Index For Teams Safety standards News Privacy policy
For Enterprises Our Charter Brand guidelines
Latest advancements ChatGPT login 7 Teams Security Other policies
GPT-4 Safety Systems .
Residency
DALLE 3 API Preparedness
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Sora Platform overview Superalignment
Pricing
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APl login 7
Explore more
OpenAl for business
Stories
OpenAl © 2015-2024 X @O m O d o
|@ Research Products Safety Company Q
B d idel
Language and assets for using the OpenAl
brand in your marketing and communications.
About
The "OpenAl" name, the OpenAl logo, the "ChatGPT" and “GPT” brands, and other OpenAl
trademarks, are property of OpenAl. These guidelines are intended to help our partners,
resellers, customers, developers, consultants, publishers, and any other third parties
understand how to use and display our trademarks and copyrighted work in their own
assets and materials.
Powered by OpenAl badge
If you are an active OpenAl API customer building using the GPT-3.5 or GPT-4 series of our
large language models, DALL-E 2 or DALL-E 3 image generation models, or any other
OpenAl model or API, we encourage you to use our “Powered by OpenAl” badge to signify
that you use our APIs to build your product or features.


Adding a function

pageType: Application

screenPatterns:
Add & Create
Code Editor

pageType: Application Application Application Application Application

screenKeywords:
o izati .
@ M:‘Z::za fon overview v Playground New features launched in the Assistants APl 7 [ Learn more &
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Playground .
&) Playg 2 Mobbin c THREAD S 8 Logs (D
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asst_CbghojdrnjAWNHDnqPOYTdCG
Q Assistants
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{=} Batches You are an interior designer consultant
B8 storage -~
db Usage
Model
@ APlkeys
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8 Docs TooLs
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8 Vector store for Mobbin 2KB
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__ Codeinterpreter ® + Files
Functions ® + Functions
MODEL CONFIGURATION
Response format
() JSON object ®
Enter your message...
Temperature 1 m.
+
@ Help 0 @
© JohnDoe W (P Clone Updated 5/14, 4:24 PM
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|o izati .
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Switching models

pageType: Application Application Application

screenKeywords:
an) @  ChatGPT4o (o]
& ChatGPT
28 Explore GPTs & GPT-40 °
4 GPT4
p GPT-35
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< < 4 7
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2. Invite members 5
Mobbin.com workspace chats aren't used to train our models. ChatGPT can make mistakes. .
|an) @  ChatGPT4 (o]
& ChatGPT
28 Explore GPTs

< < K4 7

ChatGPT tips and Quiz me on ancient Message to comfort Experience Seoul

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tricks like a local favorite genre procrastination

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pagePatterns:
Features Page
Hero Section

pagePatterns:
Features Page
Feature Section

pagePatterns:
Features Page
Stats Section

pagePatterns:
Features Page
Hero Section
Features Page
Stats Section
Features Page
Feature Section

pageType: Marketing Marketing Marketing Marketing Marketing Marketing Marketing Marketing Marketing Marketing

screenKeywords:
® Research  Products  Safety  Company Q
GPT-4 is OpenAl's most advanced system,
producing safer and more useful responses
. EEEEnR HEER
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I\ T A
SEF EENAT 0 1
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|@ Research Products Safety Company Q
Our research Latest advancements Dy .‘{ RN
LA e o WA Sy
DT e 2 ] (jo 8
27 AE T S
Overview GPT-4 : o RN\ e
i E »e o i ok 8 R
4w 50
Index DALLE 3 B b S N AT
y N Ny
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Sora
|GPT-4 surpasses GPT-3.5 in its advanced reasoning capabilities.
GPT-3.5 GPT-4
Input Input
Andrew is free from 11 am to 3 pm, Joanne is free from noon Andrew is free from 11 am to 3 pm, Joanne is free from noon
to 2 pm and then 3:30 pm to 5 pm. Hannah is available at to 2 pm and then 3:30 pm to 5 pm. Hannah is available at
noon for half an hour, and then 4 pm to 6 pm. What are some noon for half an hour, and then 4 pm to 6 pm. What are some
options for start times for a 30 minute meeting for Andrew, options for start times for a 30 minute meeting for Andrew,
Hannah, and Joanne? Hannah, and Joanne?
Output Output
Here is a list of their availability: Andrew: 11 am - 3 pm
- Andrew: 11.am to 3 pm Joanne: 12 pm - 2 pm, 3:30 pm - 5 pm
- Joanne: noon to 2 pm, and 3:30 pm to 5 pm Hannah: 12 pm - 12:30 pm, 4 pm - 6 pm
- Hannah: noon to 12:30 pm, and 4 pm to 6 pm
Common availability for a 30-minute meeting: 12 pm - 12:30.
Based on their availability, there is a 30-minute window where PA
all three of them are available, which is from 4 pm to 4:30 pm.
So, the meeting can be scheduled at 4 pm.J]
GPT-4 outperforms GPT-3.5 by scoring in higher approximate percentiles among test-
takers.
Uniform Bar Exam Biology Olympiad
DT 2= DT A DT 2= DT A [(wwitvhh viteatiarm )
|Creativity  Visual input  Longer context
GPT-4 can accept images as
. . Input
inputs and generate captions,
classifications, and analyses. ' ) )
What can | make with these ingredients?
/
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Output
There are many options for what you can make with these
ingredients! Some possibilities include:
- Pancakes or waffles
- Crepes
- French toast
|Built with GPT-4
We've collaborated with organizations building innovative products with GPT-4.
>
Story
duolingo
GPT-4 deepens the conversation on Duolingo.
Climate
@ Policy Material ® mem Harvey. sfee Speak
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GPT-4 can solve difficult problems with greater accuracy, thanks to its broader general
knowledge and problem solving abilities.
Creativity  Visual input  Longer context
|More on GPT-4
Research
GPT-4 is the latest milestone in OpenAl’s effort in scaling up deep learning.
View GPT-4 research
Infrastructure
GPT-4 was trained on Microsoft Azure Al supercomputers. Azure’s Al-optimized
infrastructure also allows us to deliver GPT-4 to users around the world.
Limitations
GPT-4 still has many known limitations that we are working to address, such as social
biases, hallucinations, and adversarial prompts. We encourage and facilitate transparency,
user education, and wider Al literacy as society adopts these models. We also aim to
expand the avenues of input people have in shaping our models.
Availability
GPT-4 is available on ChatGPT Plus and as an API for developers to build applications and
services.
View contributions

‘Alf\,lﬁf\ I\\If\:+f\f4 +I\ P Y aoaVWal I!'\I'\\A I V\I\I‘\V\If\ I aYal
|GPT-4 outperforms GPT-3.5 by scoring in higher approximate percentiles among test-
takers.
Uniform Bar Exam Biology Olympiad
GPT-3.5 GPT-4 GPT-3.5 GPT-4 (with vision)
Following the research path from GPT, GPT-2, and
GPT-3, our deep learning approach leverages more
data and more computation to create increasingly
sophisticated and capable language models.
|We spent 6 months making GPT-4 safer and more aligned.
GPT-4is 82% less likely to respond to requests for disallowed
content and 40% more likely to produce factual responses
than GPT-3.5 on our internal evaluations.
Safety & alignment
Training with human feedback We incorporated more human feedback, including
feedback submitted by ChatGPT users, to improve GPT-4’s behavior. We also worked with
over 50 experts for early feedback in domains including Al safety and security.
Continuous improvement from real-world use We've applied lessons from real-world use
of our previous models into GPT-4's safety research and monitoring system. Like ChatGPT,
we’ll be updating and improving GPT-4 at a regular cadence as more people use it.
GPT-4-assisted safety research GPT-4’s advanced reasoning and instruction-following
capabilities expedited our safety work. We used GPT-4 to help create training data for
model fine-tuning and iterate on classifiers across training, evaluations, and monitoring.
Built with GPT-4
We've collaborated with organizations building innovative products with GPT-4.
>
l
|GPT-4 can solve difficult problems with greater accuracy, thanks to its broader general
knowledge and problem solving abilities.
Creativity  Visual input  Longer context
GPT-4 is more creative and
collaborative than ever before. Input
It can generate, edit, and
iterate with users on creative Explain the plot of Cinderella in a sentence where each word
and technical writing tasks has to begin with the next letter in the alphabet from A to Z,
such as composing songs, without repeating any letters.
writing screenplays, or learning
a user's writing style.
Output
A beautiful Cinderella, dwelling eagerly, finally gains
happiness; inspiring jealous kin, love magically nurtures
opulent prince; quietly rescues, slipper triumphs, uniting very
wondrously, xenial youth zealously.J]
GPT-4 surpasses GPT-3.5 in its advanced reasoning capabilities.
GPT-3.5 GPT-4
Input Input
Andrew is free from 11 am to 3 pm, Joanne is free from noon Andrew is free from 11 am to 3 pm, Joanne is free from noon
to 2 pm and then 3:30 pm to 5 pm. Hannah is available at to 2 pm and then 3:30 pm to 5 pm. Hannah is available at
noon for half an hour, and then 4 pm to 6 pm. What are some noon for half an hour, and then 4 pm to 6 pm. What are some
options for start times for a 30 minute meeting for Andrew, options for start times for a 30 minute meeting for Andrew,
Hannah, and Joanne? Hannah, and Joanne?


Sora

screenElements: Photo Carousel

pageType: Marketing Marketing Marketing Marketing Marketing Marketing Marketing

screenKeywords:
@ Research Products Safety Company Q
Creating video from text
Sorais an Al model that can create realistic
and imaginative scenes from text instructions.
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Sora
|Sora
|Research Leads
Bill Peebles & Tim Brooks
Systems Lead
Connor Holmes
Core Contributors  Clarence Ng
David Schnurr
Eric Luhman
Joe Taylor
Li Jing
Natalie Summers
Ricky Wang
Rohan Sahai
Ryan O'Rourke
Troy Luhman
Will DePue
Yufei Guo
Special Thanks
Avi Nayak, Bob McGrew, Brad Lightcap, Chad Nelson, David Medina, Gabriel Goh,
|All videos on this page were generated directly by Sora without modification.
|We’re teaching Al to understand and simulate the physical world in motion, with the goal of
training models that help people solve problems that require real-world interaction.
Introducing Sora, our text-to-video model. Sora can generate videos up to a minute long
while maintaining visual quality and adherence to the user’s prompt.
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All videos on this page were generated directly by Sora without modification.
We’re teaching Al to understand and simulate the physical world in motion, with the goal of
training models that help people solve problems that require real-world interaction.
Introducing Sora, our text-to-video model. Sora can generate videos up to a minute long
while maintaining visual quality and adherence to the user’s prompt.


Article detail

screenPatterns:
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screenElements:
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Table of Contents

screenPatterns:
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pagePatterns:
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pageType: Marketing Marketing Marketing Marketing

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&) Research  Products  Safety ~ Company Q
Reimagining secure
Infrastructure for advanced Al
|Securing advanced Al systems will require an evolution in infrastructure security. We're

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today and contribute to the protection of advanced Al.

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providers to scientists to educators — and yes, even to cybersecurity engineers. That work p Read aloud @
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begins with building secure, trustworthy Al systems that protect the underlying technology
from those who seek to subvert it.

Threat model

Al is the most strategic and sought after technology of our time. It is pursued with vigor by

sophisticated cyber threat actors with strategic aims. At OpenAl, we defend against these

threats every day. We expect these threats to grow in intensity as Al continues to increase
in strategic importance.

Protecting model weights is an important priority for many Al developers. Model weights

are the output of the model training process. Model training combines three essential

ingredients: sophisticated algorithms, curated training datasets, and vast amounts of

computing resources. The resulting model weights are sequences of numbers stored in a

file or series of files. Al developers may wish to protect these files because they embody the

power and potential of the algorithms, training data, and computing resources that went
into them.

Since nearly all of the societal utility of model weights stems from their online use, reaping

their benefits requires their online availability:

« In order to power tools like ChatGPT and the OpenAl API Platform, users must be able to
send API requests to infrastructure hosting the model weights. While hosting model
weights enables anyone with an Internet connection to harness the power of Al, it also
presents a target for hackers. » Read aloud <)


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Setting up model usage

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Creating a new project

screenElements:
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screenKeywords:
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Projects are shared environments where teams can collaborate and share

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Updating password

appName: Uxcel

appCategory: Education

appTagline: Learn UX design at your own pace

companyStage: Early Stage

screenPatterns: Error Edit

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Skill detail

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Assistants

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Prompt examples

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rompt exampies
o
o= . .
Explore what's possible with some example prompts
&
& Q_ Search... All categories <
- Grammar correction Summarize for a 2nd grader
L
@ &= Convert ungrammatical statements into Simplify text to a level appropriate for a
g standard English. second-grade student.
Parse unstructured data Emoji Translation
Create tables from unstructured text. Translate regular text into emoji text.
e Calculate time complexity # Explain code
Find the time complexity of a function. Explain a complicated piece of code.
p Keywords Product name generator
Extract keywords from a block of text. Generate product names from a description
and seed words.
Python bug fixer Spreadsheet creator
Find and fix bugs in source code. Create spreadsheets of various kinds of data.
# Tweet classifier Airport code extractor
Detect sentiment in a tweet. Extract airport codes from text.
® Ln/ Mood to color VR fitness idea generator
Turn a text description into a color. Generate ideas for fitness promoting virtual
5 reality games.


Creating a new batch

screenPatterns:
Add & Create
Upload & Download

screenPatterns:
Add & Create
Upload & Download
Progress

screenKeywords:
@ Orga_nlzatlon overview o Batches O Learn more
Mobbin
(3 Playground
batch_o0S409yH4Zql6thakOqjnstlIS 5/13/2024, 4:03 PM BATCH
Q Assistants .
batch_oS409yH4Zql6thakOqjnstJS
3 Fine-tuning
(=} Batches @® Status @ Completed
@ Storage @ Created at May 13,2024, 4:03 PM
& Usage ‘& Endpoint /vi/chat/completions
- Completionwindow  24h
@ APl keys @ Completion time 1minute, 3 seconds
@ Settings db Request counts 2 completed, O failed of 2 total requests
L Docs O Files
Input input.jsonl @
Output batch_oS409yH4Zql6thakOgjnstJS_output.jsonl & ¥
Error
MONDAY, MAY 13, 2024
16:03:02 Batch created
16:03:03 Batch in progress
16:04:05 Batch finalizing
16:04:05 Batch completed
@ Help
G John Doe ¥ Download output
|Create a batch
Input file
Add ajsonl file of request inputs for the batch.
Upload new ® Select existing
file-28KJZUjbQSAjVS5TpOGwWQqx1
Browse files 2
Completion window
The time frame within which the batch should be processed.
24 hours <
Endpoint
The endpoint to be used for all requests in the batch.
/vi/chat/completions <
Learn about the Batch APl 2 Cancel
|Create a batch
Input file
Add ajsonl file of request inputs for the batch.
@ Upload new Select existing
€:
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(.jsonl)

Completion window
The time frame within which the batch should be processed.

24 hours <
Endpoint
The endpoint to be used for all requests in the batch.

/vi/chat/completions <
Learn about the Batch APl 2 Cancel Create
|0 Organization overview Batches O Learn more
Mobbin
(3 Playground
© batch_o0S409yH4Zql6thakOqjnstJS ~ In-progress0/2 5/13/2024, 4:03 PM BATCH
Assistants .
- batch_oS409yH4Zql6thakOqjnstJS
= Fine-tuning
{z} Batches @® Status " In-progress 0/ 2
g Storage @ Created at May 13,2024, 4:03 PM
db Usage “& Endpoint /vi/chat/completions
- Completionwindow  24h
@ APl keys db Request counts 0 completed, O failed of 2 total requests
@ Settings O Files
Q Docs . .
Input input.jsonl @
Output
Error
MONDAY, MAY 13,2024
16:03:02 Batch created
16:03:03 Batch in progress
@ Help
@ JohnDoe ® Cancel batch
|Mobbin
+

@ Mobbin e Batches & Learn more
(3 Playground

Q Assistants

N Threads

= Fine-tuning

{=} Batches

@ Storage

db Usage

@ APlkeys

@ Settings

Q Docs

No batches found Select a batch to view details.
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@ Help
o John Doe


Cloning an assistant

pageType: Application Application

screenKeywords:
Default project . -
v + Create
0 Poreonal Assistants
(3 Playground Instructions
Today, May 13
D Assistants An interior design assistant
= Fine-tuning Mctbl 2:04 PM
asst_WVeWf4oBahhSxBBLsJcc6SvO N
L
{z} Batches
@ Storage Model
db Usage gpt-3.5-turbo <
@ APlkeys
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@ Settings
O Docs @ Filesearch ® + Files
g Vectorstore for Mobbin TKB
vs_ZdpHcTiEIbUzXrxDhsQssLhf
__ Codeinterpreter ® + Files
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8 get_weather
MODEL CONFIGURATION
Response format
() JSON object ®
Temperature 1.51 TopP 1
API VERSION
@ Help Latest ® Switch to v1
o John Doe
W (P Clone Updated 5/13,2:36 PM
|Organization overview .
[ ik v Assistants
obbin
(3 Playground
Today, May 13 ASSISTANT
@ Assistants
- Cooy of Mobbi asst_p6WVxpoln8uGw9fzYOXXxyOq Playground 7
= Fine-tuning opy of Mobbin 3:35PM
asst_pBWVxpoln8uGw9fzYOXXxyOq
{z} Batches Name
g Storage Mobbin 318 PM Copy of Mobbin
asst_xAqQxpDyOFOzfAkFfgOmAFc5 asst_pBWVxpoLn8uGHIE£ZYOXXxy0q
db Usage
Instructions
@ APl keys You are an interior designer consultant
@ Settings
L‘l
Q Docs
Model
gpt-4-turbo ]
TOOLS
@ Filesearch ® + Files
8 Vector store for Mobbin TKB
vs_SIpEPIXXqnSXMIQvX62Z5mst
Code interpreter ® + Files
Functions ® + Functions
8 get_stock_price
MODEL CONFIGURATION
Response format
@ Help
JSON object ®
G John Doe
W Y Clone Updated 5/13, 3:35 PM


Creating a fine-tuned model

screenElements: Icon Badge

screenPatterns:
Other Content
Multi-Column Layout

screenPatterns:
Empty State
Other Content
Multi-Column Layout

pageType: Application Application Application Application Application Application Application Application Application Application

screenKeywords:
Create a fine-tuned model
Base Model
gpt-3.5-turbo-0125 <
Training data
Add a jsonl file to use for training.
Upload new ® Select existing
file-IkFxuP12ef5qbKL3uTrwdGO6
Browse files 7
Validation data
Add ajsonl file to use for validation metrics.
Upload new Select existing ® None
Suffix
Add a custom suffix that will be appended to the output model name.
my-experiment
Seed
The seed controls the reproducibility of the job. Passing in the same seed and job
parameters should produce the same results, but may differ in rare cases. If a seed is not
specified, one will be generated for you.
Random
Configure hyperparameters
Batch size © auto
Learning rate multiplier ® auto
In most cases, range of 01-10 is recommended.
Number of epochs © auto
|Create a fine-tuned model
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gpt-3.5-turbo-0125 <

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@ Upload new Select existing

€:
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(.jsonl)
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Add ajsonl file to use for validation metrics.
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Add a custom suffix that will be appended to the output model name.

my-experiment
Seed
The seed controls the reproducibility of the job. Passing in the same seed and job
parameters should produce the same results, but may differ in rare cases. If a seed is not
specified, one will be generated for you.

Random
Configure hyperparameters
Batch size © auto
Learning rate multiplier ® auto

In most cases, range of 01-10 is recommended.
|Create a fine-tuned model
Base Model
BASE MODELS
babbage-002
davinci-002
gpt-3.5-turbo-0125
gpt-3.5-turbo-0613
gpt-3.5-turbo-1106
Validation data
Add ajsonl file to use for validation metrics.
Upload new Select existing ® None
Suffix
Add a custom suffix that will be appended to the output model name.
my-experiment
Seed
The seed controls the reproducibility of the job. Passing in the same seed and job
parameters should produce the same results, but may differ in rare cases. If a seed is not
specified, one will be generated for you.
Random
Configure hyperparameters
Batch size © auto
Learning rate multiplier ® auto
In most cases, range of 01-10 is recommended.
|Training data
Add a jsonl file to use for training.
Upload new ® Select existing
file-IkFxuP12ef5qbKL3uTrwdGO6
Browse files 7
Validation data
Add ajsonl file to use for validation metrics.
Upload new Select existing ® None
Suffix
Add a custom suffix that will be appended to the output model name.
Sales
Seed
The seed controls the reproducibility of the job. Passing in the same seed and job
parameters should produce the same results, but may differ in rare cases. If a seed is not
specified, one will be generated for you.
Random
Configure hyperparameters
Batch size © auto
Learning rate multiplier ® auto
In most cases, range of 01-10 is recommended.
Number of epochs © auto
In most cases, range of 1-10 is recommended.
Learn about fine-tuning 2 Cancel
|Organization overview . .
@ obbin v Fine-tuning
All Successful Failed & Learn more
(3 Playground
Q Assistants
Z Fine-tuning gpt-3.5-turbo-0125 . Fine-tuning... 5/13/2024, 4:10 PM MODEL
{5} Batches gpt-3.5-turbo-0125 ) Fine-tuning...
gpt-3.5-turbo-0125 ~ @ Failed 5/13/2024, 4:09 PM
8 storage ® JobID ftjob-qASdbaeY065IwimIEglgL1yW
db Usage gpt-3.5-turbo-0125 ~ @ Failed 5/13/2024, 3:44 PM © Base model gpt-3.5-turbo-0125
) @ Created at May 13,2024, 4:10 PM
& APlkeys gpt-3.5-turbo-0125:Sales =~ @ Failed 5/13/2024, 3:43 PM
@ Estimated finish May 13, 2024, 4:24 PM
@ Settings
O Docs 88 Trained tokens -
< Epochs 3
S Batchsize 1
db LR multiplier 2
$? Seed 793790981
O Files
Training helper-example-json-clean.jsonl @
Validation -
db Training loss 1.4512
6
4
) \/\h
o
1 3 5 8
G John Doe ® Cancel job © Copy Job
|Mobbin . .
@ Mobbin v Fine-tuning
All Successful Failed & Learn more
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Q Assistants
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3 Fine-tuning
{z} Batches
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® Help
o John Doe
|@ (’;;?jzir;ization overview o Fine-tuning
& Playground All Successful Failed & Learn more
Q Assistants
Z Fine-tuning ft:gpt-3.5-turbo-0125:mobbin::90MBVuKf 5/13/2024, 4:10 PM MODEL
(5} Batches ft:gpt-3.5-turbo-0125:mobbin::90MBVUKf @ succeeded
gpt-3.5-turbo-0125 =~ ® Failed 5/13/2024, 4:09 PM
8 storage ® JobID ftjob-qASdbaeY065IwimIEglgLiyW
db Usage gpt-3.5-turbo-0125 | © Failed 5/13/2024, 3:44 PM @ Base model gpt-3.5-turbo-0125
@ Output model ft:gpt-3.5-turbo-0125:mobbin: : 90MBVuK£E
& APlkeys gpt-3.5-turbo-0125:Sales =~ @ Failed 5/13/2024, 3:43 PM
@ Created at May 13,2024, 4:10 PM
@ Settings
O Dbocs 88 Trained tokens 19,152
< Epochs 3
£ Batchsize 1
db LR multiplier 2
2 Seed 793790981
&) Checkpoints
ft:gpt-3.5-turbo-0125:mobbin: :90MBVtEf:ckpt-step-85
ft:gpt-3.5-turbo-0125:mobbin: :90MBVfoIl:ckpt-step-170
ft:gpt-3.5-turbo-0125:mobbin: : 90MBVuK£E
O3 Files
Training helper-example-json-clean.jsonl @
Validation -
db Training loss 0.0988
6
4
@ Help A \
© JohnDoe © Copy Job Playground (3
|Create a fine-tuned model
Base Model
gpt-3.5-turbo-0125 <
Training data
Add a jsonl file to use for training.
Upload new ® Select existing
file-IkFxuP12ef5qbKL3uTrwdGO6
Browse files 7
Validation data
Add ajsonl file to use for validation metrics.
Upload new Select existing ® None
Suffix
Add a custom suffix that will be appended to the output model name.
Sales
Seed
The seed controls the reproducibility of the job. Passing in the same seed and job
parameters should produce the same results, but may differ in rare cases. If a seed is not
specified, one will be generated for you.
Random
Configure hyperparameters
Batch size © auto
Learning rate multiplier ® auto
In most cases, range of 01-10 is recommended.
Number of epochs © auto
|Create a fine-tuned model
Base Model
Select... ¢

Training data
Add a jsonl file to use for training.

@ Upload new Select existing

€:
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Add ajsonl file to use for validation metrics.
Upload new Select existing ® None

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Add a custom suffix that will be appended to the output model name.

my-experiment
Seed
The seed controls the reproducibility of the job. Passing in the same seed and job
parameters should produce the same results, but may differ in rare cases. If a seed is not
specified, one will be generated for you.

Random
Configure hyperparameters
Batch size © auto
Learning rate multiplier ® auto

In most cases, range of 01-10 is recommended.
|Training data
Add a jsonl file to use for training.
Upload new ®) Select existing
file-9hsj65UNmivDVz6nrsA4vUlb
Browse files 7
Validation data
Add ajsonl file to use for validation metrics.
Upload new Select existing ®) None
Suffix
Add a custom suffix that will be appended to the output model name.
Sales
Seed
The seed controls the reproducibility of the job. Passing in the same seed and job
parameters should produce the same results, but may differ in rare cases. If a seed is not
specified, one will be generated for you.
1
Configure hyperparameters
Batch size © auto
Learning rate multiplier ® auto
In most cases, range of 01-10 is recommended.
Number of epochs © auto
In most cases, range of 1-10 is recommended.
Learn about fine-tuning 2 Cancel ) Creating...


View code

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ASSISTANT ASSISTANT
Sure, here’s a comprehensive and holistic omnichannel marketing plan for Sure, here’s a comprehensive and holistic omnichannel marketing plan for
mobbin.com, the world's largest mobile and web design inspiration library. mobbin.com, the world's largest mobile and web design inspiration library.
Latency 3554ms - 1097 tokens Latency 7528ms - 838 tokens
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(& APlkeys 62 3
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POST /vi/chat/completions nodejsv (P
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@ Assistants Android & Web des 1 import OpenAI from "openai'; In reference library - The world's largest mobile & web
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4 : process.env.OPENAI_API_KEY,
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25 3},
26 {
27 "type": "image_url",
28 "image_url": { Latency 7528ms - 838 tokens
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subscribers, free trial users, and premium members. users about design and promote email sign-ups.
Completions - **Segmentation**: Segment email lists based on user behavior and - **Webinars and Live Streams**: Host monthly sessions with industry
@ Assistants preferences to deliver targeted content. leaders to discuss design strategies and innovations.
2 Fine-tuning - **Re-engagement**: Implement a re-engagement campaign for
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() Batches - **Regular Posting**: Share tips, trends, and new library additions on
B storage ### 5. **Paid Advertising** platforms like Instagram, Twitter, LinkedIn, and Facebook.
db Usage - **Google Ads**: Utilize Google Search and Display Ads targeted at - **Engagement**: Run contests and community challenges to
relevant keywords and interests. encourage user interaction.
- **Social Media Ads**: Run ads on Facebook, Instagram, LinkedIn, and - **|nfluencer Partnerships**: Collaborate with design influencers to
@ APIkeys Twitter targeting design professionals. widen reach.
£33 Settings - **Retargeting**: Implement retargeting campaigns to re-engage users
0 Docs who visited the site but didn’t convert. ### 4. **Email Marketing**
- **Newsletter**: Weekly newsletters featuring the latest posts, library
### 6. **Partnerships and Collaborations** updates, and exclusive content.
- **Design Communities**: Partner with online design communities like - **Targeted Campaigns**: Segment the user base to deliver
Awwwards, Behance, and Dribbble. personalized messages based on behavior and preferences.
- **Corporate Partnerships**: Collaborate with design tools and
platforms like Sketch, Figma, Adobe XD for co-promotional opportunities. ### 5. **Paid Advertising**
- **Educational Institutions**: Partner with design schools and - **Google Ads**: Target high-intent keywords relevant to UlI/UX design
universities for student discounts and collaborations. and web development.
- **Social Media Ads**: Use platforms like Facebook and LinkedIn for
### 7. **Public Relations and Thought Leadership** targeted ads aimed at design professionals and agencies.
- **Press Releases - **Ret
Latency 3554ms - 1097 tokens Latency 7528ms - 838 tokens
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News

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Switching to Teams

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Copying a code snippet

screenKeywords:
@ @& ChatGPT4o S Q)
Generate a code for simple slot game
&) Here's a simple implementation of a slot machine game in Python. This code simulates a basic slot
machine where a player can spin the reels and see if they win based on matching symbols.
python (3 Copy code
import random
symbols = ["Cherry", "Lemon", "Orange", "Plum", "Bell", "Bar"]
def (0):
reell = random.choice(symbols)
reel2 = random.choice(symbols)
reel3 = random.choice(symbols)
return reell, reel2, reel3
def (reels):
if reels[0] == reels[1] == reels[2]:
return True
return False
def ():
print("Welcome to the Slot Machine Game!")
balance =
play_again = "y"
while play_again.lower() == "y" 01 balance > 0:
print(f"Current Balance: ${balancel}")
?
Mobbin.com workspace chats aren't used to train our models. ChatGPT can make mistakes. .
|@ @& ChatGPT4o S Q)
Generate a code for simple slot game
&) Here's a simple implementation of a slot machine game in Python. This code simulates a basic slot
machine where a player can spin the reels and see if they win based on matching symbols.
python v Copied!
import random
symbols = ["Cherry", "Lemon", "Orange", "Plum", "Bell", "Bar"]
def (0):
reell = random.choice(symbols)
reel2 = random.choice(symbols)
reel3 = random.choice(symbols)
return reell, reel2, reel3
def (reels):
if reels[0] == reels[1] == reels[2]:
return True
return False
def ():
print("Welcome to the Slot Machine Game!")
balance =
play_again = "y"
while play_again.lower() == "y" 01 balance > 0:
print(f"Current Balance: ${balancel}")
?
Mobbin.com workspace chats aren't used to train our models. ChatGPT can make mistakes. .


Taking a tour

screenElements:
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pagePatterns:
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screenElements:
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pagePatterns:
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Submitting a design brief

actions:
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Selecting & Choosing
Uploading & Downloading

screenElements:
Text Field
Toolbar

screenPatterns: Publish Confirmation

screenElements:
Stacked List
Divider

screenPatterns:
Reviews & Ratings
Date & Time

screenElements:
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Text Field
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screenPatterns:
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Feature Info
Empty State

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screenKeywords:
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For everyone

pagePatterns:
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screenElements:
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pagePatterns:
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Completing onboarding checklist

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.e Personalize your team prortiie
Getting Started ~ -
° 9 Make sure that your Uxcel Teams profile aligns with your company's branding.
(B Dashboard
@ R . New team member invitations or screening assessments will feature your team's logo. Make
:Q Reporting .
sure to add your team logo to your profile to stand out.
A7 Rankings
v Screening BETA Upload Logo
3 Members ° Invite team members
ARG You need to invite at least 1 other member to your team.
Send your first assignment
® Help Center ® +
Add at least 1 learning assignment to any member of your team.
J Live Chat
® &
Help Center Talk to an expert
Everyone needs help sometimes. If you get stuck Get in touch with a seasoned expert from our
or need assistance with your Uxcel Teams sales or product team to get the help you need.
onboarding experience, be sure to check out our We're here to help make your Uxcel Teams
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