Private LLMs: Power Secure AI-Driven Workflows
Datasaur supports many types of span labeling. We've set up one of our most popular project types - NER labeling.
To start labeling, click or highlight span of tokens (words) to label them. Feel free to play around with the ML-assisted extension. We also make labeling more efficient by providing keyboard shortcuts.
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Datasaur offers robust LLM tools to enhance your models. Here is a preview of how you can see the completions from your models.
You can run the provided prompt and obtain generated completions.
Prompt 1
What’s the difference between proprietary and open-source foundation models?
Result from OpenAI GPT4o
Proprietary foundation models and open-source foundation models differ mainly in terms of accessibility and control. Proprietary models are developed and maintained by organizations or companies, and their inner workings, source code, or data are typically kept confidential; you usually need a license or permission to use them. These models often come with strong support and extensive resources from their developers. On the other hand, open-source foundation models are made available to the public with their source code freely accessible, allowing anyone to use, modify, and distribute them. Open-source models foster collaboration and transparency within the community, enabling users to contribute to improvements and innovations. Essentially, it boils down to the trade-off between accessibility and support for proprietary models versus the freedom and community-driven development of open-source ones.
Result from AWS Bedrock Claude 3.5
Hey there! Great question about foundation models. The main difference between proprietary and open-source models comes down to access and transparency. Proprietary models, like GPT-3, are developed by private companies and have restricted access - you typically need to pay to use them and can't see the underlying code or training data. Open-source models, on the other hand, are freely available for anyone to use, modify, and build upon. Their code and often their training data are publicly accessible, allowing for more transparency and community involvement in their development. Both types have their pros and cons, but open-source models tend to foster more innovation and collaboration across the AI community. Hope that helps explain the key differences!
Prompt 2
My AC is out. What are other ways to stay cool this weekend?
Result from OpenAI GPT4o
Oh no, I'm sorry to hear about your AC! There are still plenty of ways to beat the heat though. You could try using fans strategically by placing a bowl of ice in front of them to cool the breeze. Drink lots of cold water to stay hydrated and eat lighter meals, like fresh salads or fruits that require no cooking. Closing curtains or blinds during the hottest parts of the day can help keep your space cooler. If it gets too warm inside, maybe spend some time at a local pool, library, or a favorite coffee shop with good air conditioning. Stay cool and take it easy!
Explore more about our LLM features
Discover the capabilities of Datasaur for LLM development. An advanced solution for Large Language Model Development built to handle even your most complex requirements, providing a personalized and efficient approach.
Start crafting your own model
Save time and effort to craft your own model with our intuitive labeling interface, designed specifically for LLM projects.