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StableBeluga2 ✓

Democratize AI through open source and science

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Chatbot Text Generation Natural Language Processing
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Automated Responses Conversational AI Customer Support Chatting
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Verdict

A quick read before you dig into the full page.

Best if
Democratize AI through open source and science
Skip if
Limited to chat, Q&A tasks
Pick this when
Fine-tuned on Llama2 70B

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Overview

StableBeluga2 is an auto-regressive language model developed by Stability AI and fine-tuned on the Llama2 70B dataset. It is designed to generate text based on user prompts.

The model can be used for various natural language processing tasks such as text generation and conversational AI. To use StableBeluga2, developers can import the necessary modules from the Transformers library and use the provided code snippet.

The model takes a prompt as input and generates a response based on the prompt. The prompt format includes a system prompt, user prompt, and assistant output.

The model supports customization through parameters such as top-p and top-k to control the output.StableBeluga2 is trained on an internal Orca-style dataset and fine-tuned using mixed-precision (BF16) training and optimized with AdamW.

The model details include information on the model type, language (English), and the HuggingFace Transformers library used for implementation.It is important to note that like other language models, StableBeluga2 may produce inaccurate, biased, or objectionable responses in some instances.

Therefore, developers are advised to perform safety testing and tuning specific to their applications before deploying the model. For further information or to get support, developers can contact Stability AI via email.

The model also includes citations for referencing and further research.

StableBeluga2 website

Access & connections

Where you can use StableBeluga2.

Platforms

Web

Capabilities

What this tool accepts, produces, and is strongest at.

Input

  • API
  • Code
  • Text

Output

  • Code
  • API
  • Text

Pros & cons

Pros

  • Fine-tuned on Llama2 70B
  • Supports text generation
  • Built with Transformers library
  • Prompt-based input
  • Customizable output parameters
  • Trained on Orca-style dataset
  • Uses mixed-precision training
  • Optimized with AdamW
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  • Available on Hugging Face
  • Accessible through code snippet
  • Supports Python coding
  • Provided citations for referencing
  • Well-documented model details
  • Good dataset diversity
  • Allows safe tuning
  • Community support available
  • Training procedure detailed
  • Clear prompt format
  • Supports English language
  • Strong performance record
  • Ethical considerations outlined
  • Used for varied tasks
  • Can process large text
  • Community-driven usability
  • Used in multiple spaces
  • Model card available
  • Variety of hyperparameters
  • Works with low CPU memory
  • Can work on auto device
  • Batch-size customization

Cons

  • Requires specific prompt format
  • Potential for objectionable responses
  • Fine-tuned model licensing restrictions
  • Only English language support
  • Reliance on HuggingFace Transformers
  • Dependent on Orca-style dataset
  • Limited to chat, Q&A tasks
  • Non-commercial usage limitation
Show 2 more
  • Needs manual safety testing
  • Highly specific optimization parameters

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Releases 1

Initial release July 28, 2023 Current
Initial release of StableBeluga2.

FAQ 12

What is the StableBeluga2 AI tool?
StableBeluga2 is an auto-regressive language model developed by Stability AI. It is designed to generate text based on user prompts and can be used for various natural language processing tasks like text generation and conversational AI.
How does StableBeluga2 generate text?
StableBeluga2 generates text based on a given user prompt. It takes a prompt as an input and generates a response accordingly using the auto-regressive language model.
What language does StableBeluga2 use for text generation?
StableBeluga2 uses English for text generation.
What library is used in the implementation of the StableBeluga2?
The HuggingFace Transformers library is used in the implementation of the StableBeluga2 model.
How do I customize the output of StableBeluga2?
You can customize the output of StableBeluga2 by adjusting the parameters such as top-p and top-k. The top-p parameter controls the nucleus sampling, and the top-k parameter controls the beam search during text generation.
How does one incorporate StableBeluga2 into their code?
StableBeluga2 can be incorporated into your code by importing the necessary modules from the Transformers library and using the provided code snippet. This includes defining the system prompt, user prompt, and setting up the assistant output.
What is the training process for StableBeluga2?
StableBeluga2 is trained via supervised fine-tuning on an internal Orca-style dataset. Its training procedure involves mixed-precision (BF16) training and optimization via AdamW.
What specific format does StableBeluga2 prompt need?
The prompt for StableBeluga2 follows a specific format that includes a system prompt, a user prompt, and an assistant output.
What kind of dataset was StableBeluga2 trained on?
StableBeluga2 was trained on an internal Orca-style dataset.
What testing steps should be conducted before StableBeluga2 deployment?
Before deploying StableBeluga2, developers are advised to conduct safety testing and tuning specific to their applications. This is to ensure safety and prevent inaccurate, biased, or potentially objectionable outputs.
What are some potential risks and limitations of StableBeluga2?
StableBeluga2 is a new technological tool and carries some risks. In some instances, it may produce inaccurate, biased, or objectionable responses. The testing conducted to date has been in English only, and not all scenarios could be covered. Hence, its potential outputs cannot be predicted in advance.
Are there any other versions of the StableBeluga model?
Yes, there are other versions of the StableBeluga model. These include StableBeluga 1 - Delta, StableBeluga 13B, and StableBeluga 7B.
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