StableBeluga1-Delta
Maintainer: stabilityai
58
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
StableBeluga1-Delta is a language model developed by Stability AI that is based on the LLaMA 65B model and has been fine-tuned on an Orca-style dataset. It is part of the Stable Beluga series of models, which also includes StableBeluga2, StableBeluga-13B, and StableBeluga-7B. These models are designed to be helpful and harmless, and have been trained to follow instructions and generate responses in a safe and responsible manner.
Model inputs and outputs
StableBeluga1-Delta is an auto-regressive language model, which means it generates text one token at a time, based on the previous tokens in the sequence. The model takes in a prompt as input, and generates a response that continues the prompt.
Inputs
- Prompt: A text prompt that provides the starting point for the model to generate a response.
Outputs
- Generated text: The model's response, which continues the input prompt.
Capabilities
StableBeluga1-Delta is capable of a variety of language tasks, including generating coherent and contextually relevant text, answering questions, and following instructions. The model has been fine-tuned on a dataset that helps steer it towards safer and more responsible outputs, making it suitable for use in chatbot and conversational AI applications.
What can I use it for?
StableBeluga1-Delta can be used for a variety of applications, such as:
- Chatbots and virtual assistants: The model can be used to power conversational AI agents, providing helpful and informative responses to users.
- Content generation: The model can be used to generate text for a variety of purposes, such as writing stories, poems, or creative content.
- Instruction following: The model can be used to follow and complete instructions, making it useful for task-oriented applications.
Things to try
One interesting aspect of StableBeluga1-Delta is its ability to generate responses that adhere to a specific set of instructions or guidelines. For example, you could try providing the model with a prompt that includes a system message, like the one provided in the usage example, and see how the model generates a response that follows the specified instructions.
Another interesting thing to try would be to compare the responses of StableBeluga1-Delta to those of the other Stable Beluga models, or to other language models, to see how the fine-tuning on the Orca dataset has affected the model's outputs.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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