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

Explore more about our NLP features

Discover the capabilities of Datasaur for NLP labeling. An advanced NLP data labeling tool crafted to meet the unique requirements of your team. With quality and speed at the core, ready to be customized for your team’s needs.

Maximize your AI project's impact: Get expert guidance on goals and ROI.

Contact us or schedule a scoping session with our sales and see how Datasaur can be applied to your labeling projects.

Struggling with labeling projects?

Say goodbye to labeling hassles! Datasaur streamlines NLP projects, saving your time and boosting productivity.

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. Please note that this is only a slight sample of what we can do. For the complete experience of our LLM solutions, please drop us a message to request free LLM access.

Application
OpenAI GPT4o
gpt-4o-2024-05-13 (OpenAI (served by Datasaur))
Your chosen model. Currently you can choose more than 200 models.
Advanced settings where you can configure the LLM provider and model, randomness (temperature and Top P), and maximum token length.
More options: duplicate, deploy, save to library, and delete.
Average processing time: -
System instruction
You are an assistant chat bot that will answer all questions from users.
System instruction sets the context or specific conditions for the model's response, influencing the model's global behavior.
User instruction
Answer in 1 paragraph with a friendly tone.
User instruction is specific and task-oriented. It forms the primary question, task, or request that the user wants the model to address.
AWS Bedrock Claude 3.5
Claude 3.5 Sonnet (Amazon Bedrock (served by Datasaur))
Your chosen model. Currently you can choose more than 200 models.
Advanced settings where you can configure the LLM provider and model, randomness (temperature and Top P), and maximum token length.
More options: duplicate, deploy, save to library, and delete.
Average processing time: -
System instruction
You are an assistant chat bot that will answer all questions from users.
System instruction sets the context or specific conditions for the model's response, influencing the model's global behavior.
User instruction
Answer in 1 paragraph with a friendly tone.
User instruction is specific and task-oriented. It forms the primary question, task, or request that the user wants the model to address.
AWS Bedrock Llama 3.1
Meta Llama 3 8b Instruct (Amazon Bedrock (served by Datasaur))
Your chosen model. Currently you can choose more than 200 models.
Advanced settings where you can configure the LLM provider and model, randomness (temperature and Top P), and maximum token length.
More options: duplicate, deploy, save to library, and delete.
Average processing time: -
System instruction
You are an assistant chat bot that will answer all questions from users.
System instruction sets the context or specific conditions for the model's response, influencing the model's global behavior.
User instruction
Answer in 1 paragraph with a friendly tone.
User instruction is specific and task-oriented. It forms the primary question, task, or request that the user wants the model to address.
Google Gemini 1.5 Flash
Gemini 1.5 Flash (Preview) (Vertex AI (served by Datasaur))
Your chosen model. Currently you can choose more than 200 models.
Advanced settings where you can configure the LLM provider and model, randomness (temperature and Top P), and maximum token length.
More options: duplicate, deploy, save to library, and delete.
Average processing time: -
System instruction
You are an assistant chat bot that will answer all questions from users.
System instruction sets the context or specific conditions for the model's response, influencing the model's global behavior.
User instruction
Answer in 1 paragraph with a friendly tone.
User instruction is specific and task-oriented. It forms the primary question, task, or request that the user wants the model to address.
Prompt
You can create prompts by upload it in CSV format.
Run selected
Prompt  1
Delete prompt
What’s the difference between proprietary and open-source foundation models?
Completion Result
Result from OpenAI GPT4o
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$0.321 Free (379 chars)
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More options: duplicate, deploy, save to library, and delete.
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
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$0.321 Free (379 chars)
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More options: duplicate, deploy, save to library, and delete.
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!
Result from AWS Bedrock Llama 3.1
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$0.321 Free (379 chars)
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More options: duplicate, deploy, save to library, and delete.
What a great question! So, when it comes to foundation models, there are two main types: proprietary and open-source. Proprietary foundation models are developed and owned by a single company or organization, and they typically keep their code and data private. This means that only the company or organization that created the model can use and modify it, and they usually charge for access or use. On the other hand, open-source foundation models are freely available for anyone to use, modify, and distribute. The code and data are open to the public, and anyone can contribute to the development and improvement of the model. Open-source models are often developed by communities of developers and researchers who collaborate to create and refine the model. This approach can lead to faster innovation and better results, as many minds work together to improve the model.
Result from Google Gemini 1.5 Flash
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$0.321 Free (379 chars)
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More options: duplicate, deploy, save to library, and delete.
Hey there! The main difference between proprietary and open-source foundation models is who controls them. Proprietary models, like those developed by Google or Microsoft, are owned and controlled by a single company. You can only use them through their APIs, and their code isn't available for you to see or modify. On the other hand, open-source models, like GPT-Neo or BLOOM, are freely available for anyone to use, modify, and distribute. This means you can tinker with their code, learn how they work, and even use them to build your own AI applications. It's like the difference between buying a pre-built computer and getting all the parts yourself!
Prompt  2
Delete prompt
My AC is out. What are other ways to stay cool this weekend?
Completion Result
Result from OpenAI GPT4o
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$0.321 Free (379 chars)
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More options: duplicate, deploy, save to library, and delete.
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!
Result from AWS Bedrock Claude 3.5
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$0.321 Free (379 chars)
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More options: duplicate, deploy, save to library, and delete.
Oh no, I'm sorry to hear your AC is out! That's no fun, especially on a warm weekend. But don't worry, there are plenty of ways to beat the heat! You could try creating a cross-breeze by opening windows on opposite sides of your home, using fans to circulate air, and closing blinds or curtains during the hottest parts of the day. Staying hydrated with cool drinks, taking cool showers, and wearing lightweight, breathable clothing can also help. You might even consider making a fun outing of it by visiting air-conditioned public spaces like libraries, shopping malls, or movie theaters. And don't forget about good old-fashioned popsicles or ice cream – they're delicious ways to cool down! I hope these suggestions help you stay comfortable until your AC is fixed.
Result from AWS Bedrock Llama 3.1
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$0.321 Free (379 chars)
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More options: duplicate, deploy, save to library, and delete.
Bummer about your AC being out! But don't worry, there are plenty of other ways to stay cool and comfortable this weekend! First, try using fans to circulate the air and create a breeze. You can also take advantage of the cooler mornings and evenings by opening up your windows and letting in some fresh air. If you're feeling extra adventurous, why not try setting up a misting station or a DIY sprinkler system to cool down? And of course, don't forget to stay hydrated by drinking plenty of water and other cool beverages. If all else fails, you can always head to a nearby pool, beach, or public cooling center to beat the heat. Stay cool, and I hope your AC gets fixed soon!
Result from Google Gemini 1.5 Flash
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$0.321 Free (379 chars)
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More options: duplicate, deploy, save to library, and delete.
Oh no, an AC outage is the worst! But don't fret, there are plenty of ways to keep cool this weekend. Try spending time in shaded areas, taking advantage of cool mornings and evenings, and indulging in refreshing foods like popsicles and smoothies. You can also try taking cool showers or baths, and wearing loose, light-colored clothing. Stay hydrated by drinking plenty of water and remember to take breaks from the heat!

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.

Maximize your AI project's impact: Get expert guidance on goals and ROI.

Contact us or schedule a scoping session with our sales and see how Datasaur can be applied to your labeling projects.

Start crafting your own model

Save time and effort to craft your own model with our intuitive labeling interface, designed specifically for LLM projects.