- NVIDIA unveiled two new big language model cloud AI services at the GTC 2022 event: the NeMo and BioNemo large language models.
- The NeMo LLM Service lets developers quickly adapt a number of pre-trained foundation models through the use of a training method termed rapid learning.
- The BioNeMo LLM Service now includes two additional BioNeMo language models for chemical and biology applications.
- Aside from the ability to change foundation models, LLM services provide the opportunity to use ready-made and bespoke models via a cloud API.
- Beginning next month, the NeMo LLM and BioNeMo services, as well as cloud APIs, will be available in early access.
At the GTC 2022 event, NVIDIA announced two new large language model cloud AI services, the NVIDIA NeMo Large Language Model Service and the NVIDIA BioNeMo LLM Service, that allow developers to easily adapt LLMs and deploy customized AI applications for content generation, text summarization, chatbots, code development, protein structure, and biomolecular property predictions, and more.
What NeMo and BioNemo large language models aim to achieve?
The NeMo LLM Service enables developers to swiftly adapt a variety of pre-trained foundation models on NVIDIA-managed infrastructure utilizing a training approach known as prompt learning. The NVIDIA BioNeMo Service is a cloud application programming interface (API) that extends LLM use cases beyond language and into scientific applications to help pharma and biotech businesses improve drug discovery.
Jensen Huang, founder, and CEO of NVIDIA said, “Large language models hold the potential to transform every industry. The ability to tune foundation models puts the power of LLMs within reach of millions of developers who can now create language services and power scientific discoveries without needing to build a massive model from scratch.”
NeMo LLM aims to accelerate deployments
Developers may utilize their own training data to customize foundation models ranging from 3 billion parameters to Megatron 530B, one of the world’s biggest LLMs, using the NeMo LLM Service. Compared to the weeks or months necessary to train a model from the start, the procedure takes only minutes to hours.
Prompt learning, which employs a technique known as p-tuning, is used to customize models. This enables developers to rapidly adapt foundation models originally trained with billions of data points using only a few hundred instances. Customization provides task-specific prompt tokens, which are then integrated with the foundation models to provide more accurate and relevant replies for specific use cases.
Developers may use the same model to customize many use cases and create a variety of prompt tokens. A playground feature allows for no-code experimentation and interaction with models, increasing the usefulness and accessibility of LLMs for industry-specific use cases. When ready, the adjusted models may be executed on cloud instances, on-premises systems, or via an API.
BioNeMo LLM will enable researchers to use massive models
Two new BioNeMo language models for chemistry and biology applications are included in the BioNeMo LLM Service. It helps researchers identify patterns and insights in biological sequences by supporting protein, DNA, and biochemical data.
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BioNeMo enables researchers to broaden the scope of their study by utilizing models with billions of parameters. Larger models can hold more information regarding protein structure and evolutionary links between genes and potentially develop new biomolecules for therapeutic uses.
Aside from modifying foundation models, LLM services provide the ability to employ ready-made and bespoke models via a cloud API.
This offers developers access to a wide range of pre-trained LLMs, including the Megatron 530B, as well as T5 and GPT-3 models produced using the NVIDIA NeMo Megatron framework, which is currently available in open beta to suit a wide range of applications and multilingual service needs.
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The NeMo LLM and BioNeMo services and cloud APIs will be offered in early access beginning next month. The NeMo Megatron framework is now available as a beta release from NVIDIA NGC. It is tailored to run on NVIDIA DGX Foundry and NVIDIA DGX SuperPOD, as well as accelerated cloud instances from Amazon Web Services, Microsoft Azure, and Oracle Cloud Infrastructure.
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