Microsoft’s Phi3: The New Small Language Model

Decoding the Small Language Model- Microsoft's Phi3

Introduction

In the largely expanding landscape of Artificial intelligence and its applications, large language models have grown in popularity by exhibiting their significance in different AI functionalities. Nevertheless, small language AI models are also redefining the AI world in their own way, making things more advanced and path breaking. Having said that, let us explore Microsoft's Phi3 which was launched recently and how to use it.

Microsoft's Phi3

With regards to open-source Large Language Models, Microsoft's Phi3 model was the first to come out with such groundbreaking innovation. It has also been a crucial factor behind the invention of favourite mini-models including the TPhixtral, Phi-DPO, etc. The Phi Family extends the notion of the massive model architecture of LLMs to Small Language Models and  mentions that Small Language Models demonstrate their relevance across diverse sets of tasks. Finally, the Phi 3 model is introduced by Microsoft which, as the manufacturer states, is a further model advancement over the other members of the Phi Generation.

What is inside Phi3?

The Phi-3 model developed by Microsoft has achieved distinct success. The model is called Phi-3-mini and it has a total number of parameters (3.8billion) and has more than 3.3trillion tokens. It is compact enough for mobile applications. Through the fact of its compact nature, Phi-3 mini performs astoundingly, and it is almost comparable in performance to mixtral 8x7B and GPT-3.5 which are much bigger in size. It stays ahead of the health race by competing with shining numbers of 69% on MMLU and 8.38 on MT-bench, which proves its language understanding and cognitive abilities.

Additionally, we have opted for a targeted neural network known as Phi-3-mini, which can be quantized using a 4-bit architecture using approximately 1.8GB of memory, making it well suited for incorporation into mobile devices. Leveraging training data that is an extension of the one that was used for Phi-2, made up of private web data and synthetic data, making it deliver spectacular performance.

What are the Unique Features of Phi3

Microsoft's Phi3 with its uniquely built architecture encompasses features that give you a new perspective towards language models. Some of the features include

Extended Context Length:

Thanks to the LongRope technology, the extended context length range is now 128k/2k, while the default length is twice as long, i.e., 4k.

Training Data Size and Quality:

The biggest differentiator between the Phi 3 launch and Phi 2 is the 3.3 Trillion token training data which is larger and more advanced, surpassing those used previously.

Model Variants:

Phi 3 Mini: Built on the 3.3 Billion Token (Tokenizer), with a Vocabulary Size of 32k and Tokenizing tokens using tiktoken.

Phi 3 Small (7B Version): Default setting is context length of 8k, not forgetting vocabulary size of 100k, and (GQA) with four queries occupying one key to lessen the memory footprint.

How to use Microsoft's Phi3?

So far Phi-3 is mainly focused on developers in the early access while the final product will hopefully be for everyone. Below is a simplified guide on how developers can initiate their journey with Phi-3

Platform Selection:

In addition to the different platforms, Phi-3 is available in services such as Microsoft Azure AI and Hugging Face and you will be able to access the model using the Ollama platform. Each toolset and its applicable policies for different social media platforms come into play.

Model Access:

The method you employ for installing Phi 3 will vary depending on the platform that you opt for. You might need to download an app or join an already existing service. This process is different on the particular platform, so follow their instructions.

Integration Process:

Consider Phi-3 library when applying for the task and proceed with drawing on the API or libraries offered. This process implies stringing up with the model of modeling and feeding in the data which is up to you.

Input Provision:

Once done, furnish Phi-3 with accurate questions and information. Since Phi3 is still new and evolving, please make your words explicit and well-proportioned.

Result Retrieval:

Phi-3 will make this the one thing by processing your input and generating the right response.

Benefits of Microsoft's Phi3

Cost-effective: For example, the usage of compact models is eco-sensible since it is both materially and functionally cheap to operate. They are characterized by smaller designs which then contribute to miniaturized storage and hardware thus resulting in cost savings for the majority of the users.

Offline and on-device AI: Owing to their compact characteristic, these models can be directly integrated into laptops, smartphones, and tablets provided the personal user owns these gadgets. They operate stably without an online connection, which is critical for areas with unfavorable browsing. This guarantees on-the-spot support for surgical decisions.

Swift responses: Due to the specificity of the architecture, the small language model can efficiently read the prompt and respond in a timely manner. This makes it suitable for on-time processing of prompts in sceneries where delays are unwelcome.

Customizability: Adjusting and justifying a smaller-sized AI model to the individual's necessities would most probably be considerably simpler and more affordable than using comprehensive, complex models. Users have an opportunity to create custom also, that also fit their cases and use different locations.

Conclusion: 

Conclusively, Microsoft's Phi-3 is a tremendous leap in the AI domain's dynamics, which is very easy to operate. The compact size and its design emphasizing the cost-effectiveness to both investment and operation also provide a high degree of flexibility in terms of its deployment. The possibility to use an AI model Phi-3 on devices which works independently of an internet connection enlarges the choice area and allows for the use of the AI in different sites, including those with restricted access to the internet. Furthermore, Phi-3's ultra-rapid response times and flexible customization takes it a step further as it can be used for a diverse range of use cases, from very timely ones to the ones customized precisely for the purpose.