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Ollama
fully managed by OctaByte

ChatGPT-Style Open Web UI Client for LLMs (Formerly Ollama WebUI) to Get up and running with Llama 2, Mistral, and other large language models.

Start free Ollama trial with OctaByte. Simple no-tricks Pricing, Scalable & Secure, just in $22.

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Benefits of Ollama fully managed by OctaByte

Deploy a fully managed instance of Ollama in just $22. You can relax knowing that we are taking care of installation, configuration, encryption, security, backups, live monitoring, software & OS updates.

Simple no-tricks pricing
Enjoy transparent and straightforward pricing with no hidden fees or complex terms.
No vendor lock-in
You can migrate your software and data to any where any time you want. With OctaByte you are totally free and in control.
Automated Updates
Let's save your business a lot of hassle, whilst ensuring that you get the performance and security benefits of regularly updated software and systems.
Encrypted Everything
All connections between your computer, the dashboard and your services are encrypted end-to-end with TLS, and all data is encrypted at rest.

Ollama screenshots

Ollama screenshot
Ollama screenshot

Ollama features Highlight

Intuitive Interface
Our chat interface takes inspiration from ChatGPT, ensuring a user-friendly experience.
Full Markdown and LaTeX Support
Elevate your LLM experience with comprehensive Markdown and LaTeX capabilities for enriched interaction.
Local RAG Integration
Dive into the future of chat interactions with the groundbreaking Retrieval Augmented Generation (RAG) support. This feature seamlessly integrates document interactions into your chat experience. You can load documents directly into the chat or add files to your document library, effortlessly accessing them using the # command in the prompt. In its alpha phase, occasional issues may arise as we actively refine and enhance this feature to ensure optimal performance and reliability.
RLHF Annotation
Empower your messages by rating them with thumbs up and thumbs down, facilitating the creation of datasets for Reinforcement Learning from Human Feedback (RLHF). Utilize your messages to train or fine-tune models, all while ensuring the confidentiality of locally saved data.

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