All about Anthropic Claude Sonnet 3.5

Introduction

Hi everyone, I hope the audio and video quality are good. Let's wait a few more seconds before we get started. Meanwhile, you can message here like someone can message if the audio and video quality are good. If you couldn’t hear me, I can change some settings. I just changed a few of my settings. I hope this works.

Yup, I think I can see a few viewers. I hope it should work. Thanks, team volume very quiet. Let me see if I can change some settings. How about now? I think I raised a few settings. I hope this is clear. Okay, thanks, Tim, thanks, Peter. Yeah, I can see a message. Cool, so in today's session, we will be focusing on learning CLA 3.5 Sonnet. This is a very new model. It got released like last month, 3 to 4 weeks old. This is much more powerful than almost compared to all the models. This is the most powerful model, cheaper, faster, and more accurate. I’m seeing a lot of people Started Loving like Cloud models, they are getting amazing results compared to even chat GPT and things like that. These kinds of models are available on both Amazon Beanstalk and Google Cloud Vertex AI.

For example, let's say your company, your workplace uses AWS; you can access these models in a much more secure way. Also, if your workplace uses Google Cloud, you can also access the models on Google Gardens, sorry, Vex AI has model Garden, and you can access it there. Cloud 3 Hau, Cloud 3 Opus, and Cloud 3 Sonnet are like their previous models. Recently, they launched this model, CLA 3.5 Sonnet, which is like their previous mid-level model. But if you see the performance and cost, this is very good spot compared to CLA 3 Sonnet and CLA 3 Opus.

Soon they are planning to release Cloud 3.5 Hau and Cloud 3.5 Opus. Soon they should be somewhere here, even more intelligent and effective than previous models. I’ve been using this model since from the day one of its launch. I really like the model. It's amazing, it does a lot of work, it's very helpful. I’m reading a few messages. Frank asking can this be recorded and sh, later, I’m another train, and hardly here. Okay, he says he couldn’t hear much. Yeah, this video will be available on the YouTube channel. You can watch it later, too. I’ll try to pre-process and increase volume if needed, but I hope you can hear me better right now. Okay, if you want me to increase volume, let me know I can do that. Cool, so if you see the models metrics, it's Cloud 3.5 Sonnet compared with Cloud 3 Opus, GPT 4, Gem 1.5 Pro, and Llama 400 billion parameter model. If you see the results, CLA 3.5 Sonnet is amazing in almost all the metrics other than one which is not too bad. This is really nice.

The thing I really like about this model is it is much faster than GPT-4 and Opus, cheaper, and more accurate. That's the main reason I started liking this model. Also, recently, this Cloud company is doing a lot of things every day. If you see their API and developer docs, they introduce a lot of cool things. Let me quickly login, so we will see all their new features and try to understand how to use these models using Python. Also, just recently, I launched a course on Udemy on mastering the Anthropic CLA 3.5 Python API. I just launched this course. I haven’t started publishing it anywhere. It got released just this morning. If you are interested in learning more, just message me I can give you a free coupon. It should be 100% free and you can learn it.

Messages API

To install the model, you can use the following command:

pip3 install anthropic
pip3 install python-dotenv

Place your API key in a .env file:

ANTHROPIC_API_KEY=your-api-key-here

Load the API key:

import os
from dotenv import load_dotenv

load_dotenv()
api_key = os.getenv("ANTHROPIC_API_KEY")

Initialize the client:

from anthropic import Anthropic

client = Anthropic(api_key)

To interact with the model:

response = client.messages.create(
    model="claude-3.5-sonnet-20240620",
    max_tokens=1000,
    temperature=0.7,
    messages=[
        ("role": "user", "content": "What's the best way to see the Sydney Opera House?")
    ]
)
print(response.choices[0].text)

Parameters Overview

Max Tokens

Controls the maximum length of the generated response.

response = client.messages.create(
    model="claude-3.5-sonnet-20240620",
    max_tokens=100,
    ...
)

Stop Sequences

Specify custom sequences to stop the model.

response = client.messages.create(
    model="claude-3.5-sonnet-20240620",
    max_tokens=1000,
    stop_sequences=["###"],
    ...
)

Temperature

Controls randomness in the generated output (0 = deterministic, 1 = most random).

response = client.messages.create(
    model="claude-3.5-sonnet-20240620",
    temperature=0.7,
    ...
)

Top P

Nucleus sampling for token selection based on cumulative probability.

response = client.messages.create(
    model="claude-3.5-sonnet-20240620",
    top_p=0.8,
    ...
)

Top K

Limit the number of tokens to consider based on probability.

response = client.messages.create(
    model="claude-3.5-sonnet-20240620",
    top_k=50,
    ...
)

Detailed Project Example

Fridge Project

Use an image of your fridge to get recipe ideas based on available items.

Convert image to Base64:

import base64

def load_image(file_path):
    with open(file_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')

Generate the prompt:

dietary_preference = "gluten-free"
image_base64 = load_image("fridge.jpg")
prompt = f"""
Dietary preference: (dietary_preference)
Image: ![fridge](data:image/jpeg;base64,(image_base64))
"""
response = client.messages.create(
    model="claude-3.5-sonnet-20240620",
    max_tokens=1000,
    messages=[("role": "user", "content": prompt)]
)
print(response.choices[0].text)

Keywords

Anthropic
Claude 3.5 Sonnet
Python API
Messages API
Temperature
Max Tokens
Stop Sequences
Top P
Top K
Base64

FAQ

What is Anthropic Claude 3.5 Sonnet?

CLA 3.5 Sonnet is an advanced, powerful model recently launched by Anthropic. It is known for its speed, cost-efficiency, and accuracy in natural language understanding and generation tasks.

How do I install the Anthropic Python library?

You can install it using the following command:

pip install anthropic

What parameters does the `messages.create` function require?

The messages.create function requires three parameters: model, max_tokens, and messages.

How does temperature affect the model's output?

Temperature controls the randomness in the generated response. A temperature of 0 makes the output deterministic, while a temperature closer to 1 makes it more random and creative.

Can I convert an image to a Base64 string for input to the model?

Yes, you can convert an image to a Base64 string and pass it as part of the input to the model.

How do I control when the model stops generating output?

You can control it using the max_tokens and stop_sequences parameters.

What is the recommended method to tune the model's creativity?

It is recommended to adjust the temperature parameter to control the model’s creativity. Higher values make the output more creative.

I hope this guide helps you understand and utilize the Anthropic Claude 3.5 Sonnet model effectively. If you have more questions or need a free coupon for the Udemy course, please let me know!

All about Anthropic Claude Sonnet 3.5