Getting Started with the OpenAI Playground
Summary
TLDRفي هذا الفيديو، يشرح المتحدث كيفية استخدام منصة OpenAI Playground لتجربة وتعلم كيفية توجيه النماذج اللغوية الكبيرة. يركز الفيديو على تقديم مقدمة بسيطة لواجهة المستخدم والإعدادات المتاحة في الـ Playground، مع توضيح كيفية استخدام الأنواع المختلفة من الأدوار - مثل دور النظام ودور المستخدم ودور المساعد - لتوجيه النماذج والحصول على استجابات مختلفة. يُبرز المتحدث أهمية الدقة في صياغة التعليمات للحصول على نتائج أفضل ويقدم نصائح حول كيفية استخدام الـ Playground بشكل فعال مع أمثلة من دليل هندسة التوجيه.
Takeaways
- 📘 المقدمة: النص يشرح كيفية استخدام ملعب OpenAI لتدريب النماذج النصية الكبيرة.
- 🔍 الدليل: يتضمن النص مرجعًا يشرح كيفية استعلام نماذج اللغات الضخمة.
- 🌐 الموقع: يجب زيارة platform.openai.com لإنشاء حساب واستخدام الملعب.
- 🔧 الإعداد: بعد إنشاء الحساب، يمكن الوصول إلى ملعب OpenAI من platform.openai.com.
- 🤖 النموذج الافتراضي: يتم استخدام نموذج GPT 2.5 turbo بشكل افتراضي في الدليل.
- 🔄 التنوع: يمكن تجربة أشكال مختلفة من GPT 2.5 turbo أو حتى GPT-4.
- 🎛️ الإعدادات: يحتوي الملعب على خيارات مختلفة مثل الدور النظام والدور المستخدم والدور المساعدة.
- 💬 واجهة الدردشة: يمكن استخدام واجهة الدردشة في الملعب لتفاعل مع النموذج.
- 📝 استعمال النموذج: يمكن استبدال النموذج بإدخال أمثلة من الدليل في الدور المناسب.
- 🔄 العدم الدeterministic: يمكن أن تختلف إجابات النموذج حتى لو كانت النموذجة هي نفسها.
- 📉 الدقة: يمكن أن تكون الإجابة أقصر عندما تكون النموذجة أكثر تحديدًا.
Q & A
ما الهدف من الفيديو المقدم؟
-الهدف من الفيديو هو توضيح كيفية استخدام Playground الخاص بـ OpenAI لتجربة مختلف الأمثلة المقدمة في دليل هندسة الطلبات.
ما هي الخطوات الأساسية لبدء استخدام Playground؟
-الخطوات الأساسية تشمل زيارة موقع platform.openai.com، إنشاء حساب في OpenAI، ومن ثم الوصول إلى واجهة Playground بعد تسجيل الدخول.
ما هو النموذج الافتراضي المستخدم في الأمثلة ضمن الدليل؟
-النموذج الافتراضي المستخدم في الأمثلة هو GPT-2.5 Turbo.
كيف يمكن للمرء أن يتفاعل مع النماذج المختلفة في Playground؟
-يمكن التفاعل مع النماذج المختلفة من خلال استخدام ثلاثة أدوار: دور النظام، دور المستخدم، ودور المساعد، حيث لكل منها طريقة مختلفة في التفاعل مع النموذج.
ما هو دور 'دور النظام' في التفاعل مع النماذج؟
-دور النظام يُستخدم لتحديد سلوك النموذج أو منطق معين يجب أن يتبعه النموذج عند الردود.
ما الفرق بين 'دور المستخدم' و 'دور النظام' في النتائج المتولدة؟
-النتائج المتولدة عند استخدام دور النظام عادة ما تكون أطول وأكثر تفصيلاً مقارنة بتلك المتولدة عند استخدام دور المستخدم، والتي قد تكون أقصر.
لماذا قد يختلف النص المتولد حتى عند استخدام نفس النص المطلوب؟
-النماذج غير حتمية، لذا قد تقدم نتائج مختلفة حتى عند استخدام نفس النص المطلوب، وذلك بسبب التباينات في الأدوار المستخدمة وطريقة التفاعل مع النموذج.
هل هناك طرق محددة أو مفضلة لاستخدام الأدوار المختلفة في Playground؟
-ليس هناك طريقة محددة أو مفضلة، بل يمكن استخدام الأدوار بمرونة وفقًا لاحتياجات المستخدم وما يرغب في تحقيقه من النموذج.
ما هو الجزء الأكثر أهمية في العمل مع هذه النماذج؟
-أحد الأجزاء الأكثر أهمية هو أن تكون محددًا في الطلبات، حيث أن زيادة التفاصيل والوضوح في النص المطلوب يؤدي إلى تحسين النتائج المتولدة.
ما هو الغرض من الفيديو بشكل عام؟
-الغرض من الفيديو هو تقديم مقدمة بسيطة وشرح لكيفية استخدام Playground لتجربة الأمثلة المختلفة في دليل هندسة الطلبات.
Outlines
🎓 Introduction to Using the Playground
This paragraph introduces the purpose of the video, which is to demonstrate how to use the OpenAI Playground for prompt engineering. It explains that the guide aims to help users learn how to prompt large language models for various use cases, and emphasizes the importance of getting familiar with the Playground to follow the examples in the guide. The speaker provides an overview of setting up the Playground, starting with creating an account on OpenAI's platform and navigating to the Playground interface.
🔍 Exploring Different Roles in the Playground
This paragraph delves into the Playground's interface, highlighting the different settings available, including the system role, user role, and assistant role. It discusses the use of the chat interface and how it allows interaction with language models. The speaker briefly touches on the models available, such as GPT-2.5 Turbo and GPT-4, and notes that the default settings are used for examples in the guide. A simple example is provided to illustrate how to use the Playground by copying a basic prompt from the guide and pasting it into the system role for testing.
📝 Differences Between System and User Roles
This paragraph explains the differences in outputs when using the system role versus the user role in the Playground. The speaker demonstrates how the same prompt produces different results depending on the role used, noting that the output from the user role tends to be shorter and different in content. The speaker emphasizes the non-deterministic nature of these models, which can yield varying responses even with the same prompt. The paragraph concludes by explaining the usefulness of the system role in enforcing specific behavior or logic when building an assistant.
📚 Flexibility in Prompting with the Playground
This final paragraph summarizes the flexibility of using different roles in the Playground. The speaker reiterates that both the system role and user role can be used effectively depending on the prompt and desired output. They demonstrate how adjusting the prompt specificity can lead to better and more concise results, using a sentence completion example. The paragraph ends with a reminder that the Playground allows users to experiment with prompts in various ways to achieve the best outcomes.
Mindmap
Keywords
💡دليل هندسة التلقين
💡نموذج اللغة
💡ساحة اللعب
💡التلقين
💡النماذج التوليدية
💡الدور النظامي
💡الدور المستخدم
💡عدم الحتمية
💡المرونة
💡النماذج المتنوعة
Highlights
Introduction to the OpenAI Playground for testing different prompt engineering techniques.
Explanation of how the Playground interface works, including system, user, and assistant roles.
Importance of setting up the Playground correctly by visiting platform.openai.com and signing in.
Introduction to the default model used in the guide: GPT-3.5 Turbo, with mentions of other available models.
Detailed walkthrough of copying and pasting prompts into the Playground's system role.
Discussion on the impact of different settings like temperature and top_p on model outputs.
Comparison between using the system role and the user role for generating text.
Observation that using the system role generally produces longer and more detailed outputs.
Highlight that using the user role can result in shorter, more direct responses.
Emphasis on the non-deterministic nature of language models, which produce varying outputs even with the same prompt.
Explanation of the flexibility in how system, user, and assistant roles can be leveraged for different tasks.
Note on the usefulness of the system role for enforcing specific behavior or logic in the model’s responses.
Demonstration of creating more specific prompts to get more precise and shorter responses from the model.
Encouragement to experiment with different roles and settings to fully understand how the model behaves.
Final summary that highlights the importance of specificity and experimentation when working with language models.
Transcripts
hi everyone so I am doing this recording
because I wanted to show you how to use
the open a playground so if you have
come to the prompt engineering guide
this guide is about learning how to
prompt these large language models and
in our guide we try our best to show you
with different examples and different
approaches how to prompt these models
for various use cases um but at the
beginning what we want to do is we want
to show you like basic U first steps on
how to prompt these models and for that
you really need to use a playground so
different language model providers
provide different playgrounds for their
models one of the models that we use
here in the prompt engineering guide is
the Open Eyes playground um but you can
use any other playground so what we want
to show you is how you can use the
playground to follow through the
examples that we provide in our prompt
engineering guide so for that you need
to have your playground set up so in
order for you to have the open a
playground set up what you need to do is
you need to visit platform.
open.com and you need to create an
account with openai and once you have
created that account you will see that
you're signed in uh when you go to the
platform. open.com what you see here is
documentation by default but what we
want to do is we want to go to the
actual playground so we go to playground
we click on that and here what you see
is we see a nice interface where we can
interact with different models right and
if we go back to our guide you will see
that the standard or the default model
that we are experimenting on is GPT 2.5
turbo uh you can experiment with newer
models so there are different variants
of GPT 2.5 turbo and there is even gp4
as well which is the the newer model but
so far by default we are using this
right for all of our examples unless we
explicitly say that we are using a
different model and also notice that we
have these values here I'll talk about
this in another video but for now for
this video what I want to do is just
keep it in the scope of starting the
playground and start to play around with
it with some of the examples that we
provide in our guide so we are at the
playground and just a quick intro of the
playground so what we see here is this
playground has different settings right
so there is a there is this panel here
which is a system panel which is
basically a system role and it will talk
about what system role is in a minute
and we also have user role and in
addition to that we have also assistant
role so we have three different types of
roles H that allow us to interact with
these language models in different ways
so also note that I am using here uh the
chat the chat interface right so there
are different different playgrounds here
there's assistance there's compare
there's completions as well which I
think will get uh deprecated at some
point but for now we're using the chat
playground okay and it looks something
like this
so just to take an example here of a
very simple example of how you would uh
you know how you would use the
playground to test out the different
prompts that we are providing in our
guide I'll show you very quickly here so
if you go to the the left hand side here
of the guide we have different um under
introduction we have basics of prompting
so if you go to basics of prompting
right we see there's a basic prompt so
what I'll do is I'll just kind of copy
I'll use this copy button here I'll copy
that and then I'll bring it over to the
system prompt right and then uh sorry
the system roll and then I'll just
prompt them all this way so once I have
it like this um then I can just I won't
change anything everything is again
temperature is default one topy default
one we will talk about that later on in
another video but for now what we're
going to do is just we want to test this
out right and and and I can see that
it's already producing or generating
text right so this is a generative VI
model is a text model that generates
text based on the prompt and it's
basically continuing the text the sky is
now there are different ways how you can
prompt this models because we have
different roles right we have system
role user Ro role and assistant role um
we can leverage the models in different
ways so what I'll show you here is
another way how you can go about um
interacting these chat models so I'll
remove my prompt from system rooll and
then I'll bring it over add a user rle
then I'll paste my prompt here and then
I'll submit it right and you can see
that it gave me also a continuation of
my prompt the sky is and this
continuation is a lot shorter and that's
something to note here right when we use
this prompt you know while we can do it
right with the user role and leave the
system roll empty right we can't do that
um you will see that the outputs are
very different so you can see that here
we use the user roll right this guy is
and the assistant responded with clear
and blue with fluffy white clouds
scattered across it it's very different
from this what the other example that I
showed you that uses the system roll is
producing right it's a different output
so that's something to note with these
models that they're non-deterministic
they'll give you different outputs even
though you're using the same
prompt but also because we're using the
user Ro it gave us something different
it's shorter than the previous one when
we use system rooll right so that's
something to note there's nothing that
says that you shouldn't
leverage models this way or leverage the
system rooll the system rooll is really
a useful feature if you are building out
an assistant and you want to enforce
some type of behavior you want to
enforce some type of logic in the way
the model is responding to you that's
what you will use the system rooll for
but because this was a very basic prompt
you know I just use the user role and it
is totally valid to use it this way so
it's a bit flexible in the way we're
using uh the model so I think I will
leave it at at that and for all the
examples you can pretty much do the same
so if you go through guide now you know
you can take something like this right
and you can either use the system role
or you can also use the user role here
so you can do something like something
like this and then you can say um again
complete the sentence the sky is blue on
a clear day because we were a little bit
more specific here you can see that the
assistant response was a lot shorter
because now it's a sentence right so
this is the very neat part of working
with these models that the more specific
you are the better results are going to
be so that's a quick introduction into
the playground
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