Elevate your LLM hosting experience with ML Place
The right place to host, retrain and master Large Language Models
Empower your AI projects
Easily access a vast library of LLM and machine learning models
Seamlessly manage models through our API, simplifying LLM integration
Benefit from hassle-free deployment and LLM model hosting without the need for DevOps
Engage our efficient training environment for meaningful LLM fine-tuning
Choose secure on-prem or versatile LLM cloud hosting solutions
Manage and integrate LLMs seamlessly
ML Place is a complete solution for managing LLMs that fits securely within your company's internal infrastructure and integrates LLMs into business workflows
Utilise connectors for seamless cloud or self-hosted LLM integration
Benefit from diverse LLM solutions like Llama and Mistral, tailored to your needs
Ensure optimal performance and resource use with transparent LLM hosting cost
Optimise your ML workflows
Cut costs and effort in software development with our ready-to-use services and architecture. ML Place reduces server expenses with auto-scaling and flexible cloud server creation
Enhance your ML operations efficiently with ML Place
- Use our intuitive tools for easy model comparison and decision-making
- Review and tag queries in the request history to aid in model retraining
- Conduct standard benchmarks swiftly for consistent performance evaluation
- Utilise model fine-tuning tools for ongoing model improvement
Explore robust features
ML Place is the optimal choice for enhancing your AI development and operational efficiency
Reliable and fast hosting for ML models, scalable to meet business demands
Simple management of an extensive range of models
Efficient resource use through auto-scaling and dynamic server allocation
Cost-saving server hosting diversity across different providers
Reduced workload for DevOps and MLOps, enabling your ML team to manage services independently
Training capabilities for bespoke ML models by business-oriented developers
Your journey to mastering LLM begins here
FAQs
What are the most popular and powerful LLMs?
What is LLM fine-tuning?
Fine-tuning refers to adjusting a pre-trained AI model on a specific dataset to improve its performance on particular tasks or with unique data. For insights into how LLMs function and their specific advantages for your business, contact us at contact@tovie.ai.
Can I deploy your models on my own servers?
Yes, ML Place offers flexible deployment options, including on-premises servers and private cloud environments, for enhanced data security and control. We provide support for setup and configuration. For any support, email us at contact@tovie.ai.
How do you compare to Hugging Face?
ML Place offers a corporate model marketplace, similar to Hugging Face, but for an internal environment. It simplifies managing large language models, delivering cloud and on-premise options through an advanced MLOps platform with accessible APIs, aimed at reducing DevOps workload and easing enterprise AI integration.
What types of models does ML Place support?
A: ML Place supports various large language models including GPT, BERT, T5 and more. It is compatible with models from providers like OpenAI, Anthropic, Google, Meta and others.
How does ML Place help with model evaluation and improvement?
ML Place includes tools to compare model responses easily, review request histories, conduct performance benchmarks, and fine-tune models. This allows for data-driven iteration and optimisation of your AI models over time.
What is the pricing model for ML Place?
ML Place has usage-based pricing, so you only pay for the resources and services you actually use. We offer a free trial to get started. Contact our sales team for high-volume enterprise pricing.
Can ML Place help manage open-source LLM hosting?
Absolutely, ML Place supports a variety of LLM hosting options, including open-source models. Our platform is equipped with connectors for cloud LLMs and supports various integrated LLM options like Llama, Mistral, and Mixtral.
How does ML Place integrate LLMs into business workflows?
ML Place seamlessly integrates LLMs into your business workflows, fitting securely within your company's internal infrastructure. With functionalities like model comparison tools, easy retraining, and the ability to manage a wide range of models, our platform ensures your LLMs contribute effectively to your business operations.
How to prepare data for LLM fine-tuning at ML Place?
To prepare your data for LLM fine-tuning at ML Place, ensure your dataset is clean, relevant to your business needs, and annotated if necessary. ML Place's tools can help you review and tag queries in the request history, aiding in preparing and optimising datasets for effective fine-tuning.