Today, I have the pleasure of presenting to you a technological advance that could well change your daily life as a developer, especially if like me, you are passionate about AI. Well yes, because you may think that it is essential to have a powerful machine equipped with a high-end GPU to get started in AI application development. But think again, because NVIDIA has developed a solution called NVIDIA NIMwhich allows these material constraints to be overcome.
With NVIDIA NIMyou will be able to develop whatever comes to mind and deploy the latest AI models without having to invest in expensive equipment and without worrying about the power of your computer. You no longer have any limits other than your imagination!
Indeed, NVIDIA NIM (NVIDIA Inference Microservices) uses generative AI inference microservices to simplify the deployment of AI models at scale. In other words, it gives you access to pre-trained and optimized AI models, hosted on powerful remote servers. You can therefore concentrate on the essentials, namely creating innovative applications.
NVIDIA NIM doesn't just remove hardware barriers. The platform offers a range of advanced features to meet the needs of developers in various areas:
- Multi-model PDF extraction : Process complex documents by enabling your AI systems to efficiently interpret and extract information from different types of PDFs.
- Interacting with digital humans : Create ultra-realistic AI avatars to revolutionize customer service, education or entertainment. This feature opens up new possibilities in human-machine interaction.
- Pharmaceutical applications : In the pharmaceutical sector, NVIDIA NIM facilitates the development of small molecules, demonstrating the versatility of the platform in specialized industries.
One of the major strengths of NVIDIA NIM is its extensive catalog of AI models. These models can be easily integrated into your applications via a user-friendly Python API. You can thus:
- Test API responses : Observe how models react to your queries and refine them accordingly.
- Run models locally (if hardware allows) : If you have compatible hardware, you can run some models on your own machine.
- Integrate AI capabilities into your applications : Enrich your projects with advanced features without additional complexity.
Visit the official NVIDIA AI website and sign up for the NVIDIA Developer Program. Registration is free and gives you access to many resources, including access to NVIDIA NIM.
Here is an example implementation:
from openai import OpenAI text = """ coucou j'avais mi un texte un peu long ici avant. """ client = OpenAI( base_url = "https://integrate.api.nvidia.com/v1", api_key = "" ) completion = client.chat.completions.create( model="nvidia/nemotron-4-340b-instruct", messages=[{"role":"user","content":"Résume moi le texte ci-dessous en français en 3 lignes : " + text}], temperature=0.2, top_p=0.7, max_tokens=1024, stream=False ) print(completion.choices[0].message.content) And I even made a video tutorial for you. You can also thank the Patreons, because it’s thanks to them!
That's it, you can now integrate the AI models offered by Nvidia into your projects without worrying about the underlying infrastructure.
Note that NVIDIA NIM offers developers API credits and if you want to run the models locally, as the Docker configuration is supported, it is easily transposable and guarantees consistency between different development environments.
Customization is also a key aspect of NVIDIA NIM. Developers have the ability to adjust and tweak existing templates to meet specific needs. For example, you can:
- Create AI chatbots tailored to your industry : By fine-tuning the models, you can specialize them for your field of activity.
- Develop specialized applications : Adapt pre-existing models to new tasks or domains.
For this, tools such as LoRA (Low-Rank Adaptation) can be used to fit models efficiently.
Now it’s your turn!
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