Akshay 🚀
@akshay-pachaar.bsky.social
Simplifying LLMs, MLOps, Python & Machine Learning for you! • Co-founder DailyDoseofDS • BITS Pilani • 3 Patents • ex-AI Engineer @ LightningAI
F-strings also support formatting for different data types, such as dates and times:
December 25, 2024 at 12:30 PM
F-strings also support formatting for different data types, such as dates and times:
If you need to use braces literally in an f-string, you can escape them with double braces:
December 25, 2024 at 12:30 PM
If you need to use braces literally in an f-string, you can escape them with double braces:
F-strings also support the `=` specifier, which can be handy for debugging or logging purposes.
It allows you to include the variable name and its value in the formatted string:
It allows you to include the variable name and its value in the formatted string:
December 25, 2024 at 12:30 PM
F-strings also support the `=` specifier, which can be handy for debugging or logging purposes.
It allows you to include the variable name and its value in the formatted string:
It allows you to include the variable name and its value in the formatted string:
F-strings support multiline strings using triple quotes!
It's one of my favourite features, I use it for creating prompt templates.
Here's an example:
It's one of my favourite features, I use it for creating prompt templates.
Here's an example:
December 25, 2024 at 12:30 PM
F-strings support multiline strings using triple quotes!
It's one of my favourite features, I use it for creating prompt templates.
Here's an example:
It's one of my favourite features, I use it for creating prompt templates.
Here's an example:
Need to format numbers or strings❓
F-strings support format specifiers:
F-strings support format specifiers:
December 25, 2024 at 12:30 PM
Need to format numbers or strings❓
F-strings support format specifiers:
F-strings support format specifiers:
You can also perform operations & call functions inside the braces.
This makes f-strings incredibly versatile for constructing dynamic strings with computed values.
Check this out👇
This makes f-strings incredibly versatile for constructing dynamic strings with computed values.
Check this out👇
December 25, 2024 at 12:30 PM
You can also perform operations & call functions inside the braces.
This makes f-strings incredibly versatile for constructing dynamic strings with computed values.
Check this out👇
This makes f-strings incredibly versatile for constructing dynamic strings with computed values.
Check this out👇
Simply put, f-strings are strings prefixed with 'f' that allow you to embed expressions inside string literals.
Here's an example:
Here's an example:
December 25, 2024 at 12:30 PM
Simply put, f-strings are strings prefixed with 'f' that allow you to embed expressions inside string literals.
Here's an example:
Here's an example:
f-strings were introduced in Python 3.6 and have since become a favorite among developers for their simplicity and readability.
Today, we'll start with the basics and dive into all the ninja tricks of using f-strings.
Let's go! 🚀
Today, we'll start with the basics and dive into all the ninja tricks of using f-strings.
Let's go! 🚀
December 25, 2024 at 12:30 PM
f-strings were introduced in Python 3.6 and have since become a favorite among developers for their simplicity and readability.
Today, we'll start with the basics and dive into all the ninja tricks of using f-strings.
Let's go! 🚀
Today, we'll start with the basics and dive into all the ninja tricks of using f-strings.
Let's go! 🚀
7️⃣ Evaluate finetuned T-5 small RAG program
**Notice the score, it beats a vanilla Mistral RAG 🔥
**Notice the score, it beats a vanilla Mistral RAG 🔥
December 12, 2024 at 12:30 PM
7️⃣ Evaluate finetuned T-5 small RAG program
**Notice the score, it beats a vanilla Mistral RAG 🔥
**Notice the score, it beats a vanilla Mistral RAG 🔥
6️⃣ Define a T-5 small RAG & Finetune it
The code below will perform finetuning & provide a checkpoint for the best model weights saved during the process.
Check this out👇
The code below will perform finetuning & provide a checkpoint for the best model weights saved during the process.
Check this out👇
December 12, 2024 at 12:30 PM
6️⃣ Define a T-5 small RAG & Finetune it
The code below will perform finetuning & provide a checkpoint for the best model weights saved during the process.
Check this out👇
The code below will perform finetuning & provide a checkpoint for the best model weights saved during the process.
Check this out👇
5️⃣ Evaluate RAG powered by Mistral
Let's first evaluate our RAG program that uses Mistral-7B as LLM
** Notice the score, this is what we want to beat!
Check this out👇
Let's first evaluate our RAG program that uses Mistral-7B as LLM
** Notice the score, this is what we want to beat!
Check this out👇
December 12, 2024 at 12:30 PM
5️⃣ Evaluate RAG powered by Mistral
Let's first evaluate our RAG program that uses Mistral-7B as LLM
** Notice the score, this is what we want to beat!
Check this out👇
Let's first evaluate our RAG program that uses Mistral-7B as LLM
** Notice the score, this is what we want to beat!
Check this out👇
4️⃣ Define the RAG program
Let's define a basic DSPy program which is a RAG pipeline for answer generation.
It's like defining a model that we want to finetune & evaluate.
Check this out👇
Let's define a basic DSPy program which is a RAG pipeline for answer generation.
It's like defining a model that we want to finetune & evaluate.
Check this out👇
December 12, 2024 at 12:30 PM
4️⃣ Define the RAG program
Let's define a basic DSPy program which is a RAG pipeline for answer generation.
It's like defining a model that we want to finetune & evaluate.
Check this out👇
Let's define a basic DSPy program which is a RAG pipeline for answer generation.
It's like defining a model that we want to finetune & evaluate.
Check this out👇
3️⃣ Set eval metric
DSPy provides out of the box support for many evaluation metrics & you can define a custom metric as well.
Our program is expected to produce short factoid answers & hence, exact match with the ground truth is a good eval metric here.
Check this out👇
DSPy provides out of the box support for many evaluation metrics & you can define a custom metric as well.
Our program is expected to produce short factoid answers & hence, exact match with the ground truth is a good eval metric here.
Check this out👇
December 12, 2024 at 12:30 PM
3️⃣ Set eval metric
DSPy provides out of the box support for many evaluation metrics & you can define a custom metric as well.
Our program is expected to produce short factoid answers & hence, exact match with the ground truth is a good eval metric here.
Check this out👇
DSPy provides out of the box support for many evaluation metrics & you can define a custom metric as well.
Our program is expected to produce short factoid answers & hence, exact match with the ground truth is a good eval metric here.
Check this out👇
2️⃣ Load dataset
Next we load the HotPotQA dataset for training & validation. HotPotQA dataset in available in `dspy.datasets`
Check this out👇
Next we load the HotPotQA dataset for training & validation. HotPotQA dataset in available in `dspy.datasets`
Check this out👇
December 12, 2024 at 12:30 PM
2️⃣ Load dataset
Next we load the HotPotQA dataset for training & validation. HotPotQA dataset in available in `dspy.datasets`
Check this out👇
Next we load the HotPotQA dataset for training & validation. HotPotQA dataset in available in `dspy.datasets`
Check this out👇
1️⃣ Set Up
We start by setting up the LM (Mistral-7B served using @Ollama & retriever model, RM which is ColBERTv2)
Check this out👇
We start by setting up the LM (Mistral-7B served using @Ollama & retriever model, RM which is ColBERTv2)
Check this out👇
December 12, 2024 at 12:30 PM
1️⃣ Set Up
We start by setting up the LM (Mistral-7B served using @Ollama & retriever model, RM which is ColBERTv2)
Check this out👇
We start by setting up the LM (Mistral-7B served using @Ollama & retriever model, RM which is ColBERTv2)
Check this out👇
DSPy is a framework for algorithmically optimizing LM prompts and weights.
DSPy : RAG :: PyTorch : DNNs
I'll make sure today's tutorial can be followed with minimal background knowledge!
Let's go! 🚀
DSPy : RAG :: PyTorch : DNNs
I'll make sure today's tutorial can be followed with minimal background knowledge!
Let's go! 🚀
December 12, 2024 at 12:30 PM
DSPy is a framework for algorithmically optimizing LM prompts and weights.
DSPy : RAG :: PyTorch : DNNs
I'll make sure today's tutorial can be followed with minimal background knowledge!
Let's go! 🚀
DSPy : RAG :: PyTorch : DNNs
I'll make sure today's tutorial can be followed with minimal background knowledge!
Let's go! 🚀
6️⃣ Polymorphism 🌀
This allows us to use a single interface for different data types or classes.
We can achieve this through method overriding, where a subclass provides a different implementation for a method defined in its parent class.
Let's understand with an example 👇
This allows us to use a single interface for different data types or classes.
We can achieve this through method overriding, where a subclass provides a different implementation for a method defined in its parent class.
Let's understand with an example 👇
December 10, 2024 at 12:32 PM
6️⃣ Polymorphism 🌀
This allows us to use a single interface for different data types or classes.
We can achieve this through method overriding, where a subclass provides a different implementation for a method defined in its parent class.
Let's understand with an example 👇
This allows us to use a single interface for different data types or classes.
We can achieve this through method overriding, where a subclass provides a different implementation for a method defined in its parent class.
Let's understand with an example 👇
5️⃣ Abstraction 🎭
This concept focuses on exposing only essential information to the outside world while hiding implementation details.
We use abstract classes and methods to define a common interface.
Here's an example 👇
This concept focuses on exposing only essential information to the outside world while hiding implementation details.
We use abstract classes and methods to define a common interface.
Here's an example 👇
December 10, 2024 at 12:31 PM
5️⃣ Abstraction 🎭
This concept focuses on exposing only essential information to the outside world while hiding implementation details.
We use abstract classes and methods to define a common interface.
Here's an example 👇
This concept focuses on exposing only essential information to the outside world while hiding implementation details.
We use abstract classes and methods to define a common interface.
Here's an example 👇
4️⃣ Encapsulation 🔐
Encapsulation helps to bundle data and methods inside a class, restricting direct access to certain attributes and methods.
We use private attributes/methods (with a `_` or `__` prefix) to achieve this.
Here's an example 👇
Encapsulation helps to bundle data and methods inside a class, restricting direct access to certain attributes and methods.
We use private attributes/methods (with a `_` or `__` prefix) to achieve this.
Here's an example 👇
December 10, 2024 at 12:31 PM
4️⃣ Encapsulation 🔐
Encapsulation helps to bundle data and methods inside a class, restricting direct access to certain attributes and methods.
We use private attributes/methods (with a `_` or `__` prefix) to achieve this.
Here's an example 👇
Encapsulation helps to bundle data and methods inside a class, restricting direct access to certain attributes and methods.
We use private attributes/methods (with a `_` or `__` prefix) to achieve this.
Here's an example 👇
3️⃣ Inheritance 🧬
Let's say we want to create an Electric car & don't want to define all the properties and methods of the basic Car class.
Inheritance helps us to inherit all the properties/methods of parent class & add new ones or override existing.
Check this out👇
Let's say we want to create an Electric car & don't want to define all the properties and methods of the basic Car class.
Inheritance helps us to inherit all the properties/methods of parent class & add new ones or override existing.
Check this out👇
December 10, 2024 at 12:31 PM
3️⃣ Inheritance 🧬
Let's say we want to create an Electric car & don't want to define all the properties and methods of the basic Car class.
Inheritance helps us to inherit all the properties/methods of parent class & add new ones or override existing.
Check this out👇
Let's say we want to create an Electric car & don't want to define all the properties and methods of the basic Car class.
Inheritance helps us to inherit all the properties/methods of parent class & add new ones or override existing.
Check this out👇
2️⃣ Class 🏗️
A class is like a blueprint for creating objects.
It defines a set of properties & functions (methods) that will be common to all objects created from the class.
So, we start with a simple example & follow along!
Let's define a class Car & create it's Object👇
A class is like a blueprint for creating objects.
It defines a set of properties & functions (methods) that will be common to all objects created from the class.
So, we start with a simple example & follow along!
Let's define a class Car & create it's Object👇
December 10, 2024 at 12:31 PM
2️⃣ Class 🏗️
A class is like a blueprint for creating objects.
It defines a set of properties & functions (methods) that will be common to all objects created from the class.
So, we start with a simple example & follow along!
Let's define a class Car & create it's Object👇
A class is like a blueprint for creating objects.
It defines a set of properties & functions (methods) that will be common to all objects created from the class.
So, we start with a simple example & follow along!
Let's define a class Car & create it's Object👇
We break it down to 6 important concepts:
- Object 🚘
- Class 🏗️
- Inheritance 🧬
- Encapsulation 🔐
- Abstraction 🎭
- Polymorphism 🌀
Let's take them one-by-one... 🚀
- Object 🚘
- Class 🏗️
- Inheritance 🧬
- Encapsulation 🔐
- Abstraction 🎭
- Polymorphism 🌀
Let's take them one-by-one... 🚀
December 10, 2024 at 12:30 PM
We break it down to 6 important concepts:
- Object 🚘
- Class 🏗️
- Inheritance 🧬
- Encapsulation 🔐
- Abstraction 🎭
- Polymorphism 🌀
Let's take them one-by-one... 🚀
- Object 🚘
- Class 🏗️
- Inheritance 🧬
- Encapsulation 🔐
- Abstraction 🎭
- Polymorphism 🌀
Let's take them one-by-one... 🚀
Synthetic datasets with Llama 3? It's easier than you think.
I've been playing with a Distilabel, an open-source framework that lets you generate domain-specific synthetic text data using Llama 3.
Try it yourself: lightning.ai/lightning-a...
I've been playing with a Distilabel, an open-source framework that lets you generate domain-specific synthetic text data using Llama 3.
Try it yourself: lightning.ai/lightning-a...
December 9, 2024 at 12:30 PM
Synthetic datasets with Llama 3? It's easier than you think.
I've been playing with a Distilabel, an open-source framework that lets you generate domain-specific synthetic text data using Llama 3.
Try it yourself: lightning.ai/lightning-a...
I've been playing with a Distilabel, an open-source framework that lets you generate domain-specific synthetic text data using Llama 3.
Try it yourself: lightning.ai/lightning-a...
Image to LaTeX powered by multimodal Llama 3.2!
.
.
Upload image of an equation, and it gives you the corresponding LaTeX code.
Find code here: github.com/patchy631/a...
.
.
Upload image of an equation, and it gives you the corresponding LaTeX code.
Find code here: github.com/patchy631/a...
December 8, 2024 at 12:48 PM
Image to LaTeX powered by multimodal Llama 3.2!
.
.
Upload image of an equation, and it gives you the corresponding LaTeX code.
Find code here: github.com/patchy631/a...
.
.
Upload image of an equation, and it gives you the corresponding LaTeX code.
Find code here: github.com/patchy631/a...
PydanticAI: Build production-grade Agentic AI apps in pure Python!
PydanticAI offers the same elegance and ease of use as FastAPI, now extending that experience to building production-grade LLM applications.
GitHub repo: github.com/pydantic/py...
PydanticAI offers the same elegance and ease of use as FastAPI, now extending that experience to building production-grade LLM applications.
GitHub repo: github.com/pydantic/py...
December 6, 2024 at 12:30 PM
PydanticAI: Build production-grade Agentic AI apps in pure Python!
PydanticAI offers the same elegance and ease of use as FastAPI, now extending that experience to building production-grade LLM applications.
GitHub repo: github.com/pydantic/py...
PydanticAI offers the same elegance and ease of use as FastAPI, now extending that experience to building production-grade LLM applications.
GitHub repo: github.com/pydantic/py...