Partner with {keyword} or similar agencies in Europe and LATAM

The model was deployed on a single GPU - NVIDIA A10G with 24GB VRAM - with Amazon SageMaker. This is the proposed minimum hardware requirement and does not ensure fast response time. Performance can be improved by deploying to a multi-GPU instance or opting for a smaller language model.


Deployment in AWS

- multi-GPU instance and an optimized implementation with the DeepSpeed Zero Redundancy Optimizer to reduce the memory footprint;
- task and domain specific datasets provided from internal documents or available online. 



Fine-tuning with DeepSpeed

The LangChain framework allows for an LLM to connect to data sources and easily implement different use cases such as Personal assistant information retrieval, chatbots, etc.


Use case deployment with LangChain 

The model achieves State-of-the-Art results on NLP tasks ranging from language generation, language understanding, text classification, question answering, commonsense reasoning, long text reasoning, structured knowledge grounding and information retrieval.


State-of-the-Art performance

The model allows for fine-tuning on additional datasets for specific tasks such as code generation, translation, chatbot and others. 


Fine-tuning possibilities

Learn how Prime Holding worked with SME clients and how they can support your Information Technology, Business & Expert Solutions product and team.

Prime Holding Success Story in Information Technology, Business & Expert Solutions for SME - A case study | 2024

Customizing large language models for specific business problems is challenging because there are many options, and the approaches and language are often inconsistent. The choice comes down to optimizing the prompt for a general model or fine-tuning a model on your data.


Optimization patterns

While it’s straightforward for simple use cases, when building production applications, you run into many challenges, such as ambiguity in how large language models ingest and generate results, compatibility of prompts between different large language models, and maintaining them.


Scaling prompt engineering

The client stakeholders worked closely with the team at Prime Holding

Deploying LLM at private infrastructure

Prime Holding

Large Language Model (LLM) technology will play a significant role in the development of future applications. Why not start now?