Mistral-7B-v0.3

Maintainer: mistralai

Total Score

88

Last updated 5/23/2024

⚙️

PropertyValue
Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model overview

The Mistral-7B-v0.3 is a Large Language Model (LLM) with 7 billion parameters, developed by mistralai. It is an extension of the previous Mistral-7B-v0.2 model, with an increased vocabulary size of 32,768. The Mistral-7B-v0.3 outperforms the Llama 2 13B model on various benchmarks, as detailed in the Mistral-7B-v0.1 model card.

Model inputs and outputs

The Mistral-7B-v0.3 is a text-to-text generative model, capable of producing human-like text based on the provided input.

Inputs

  • Text prompt: The model takes a text prompt as input, which it uses to generate the output.

Outputs

  • Generated text: The model outputs generated text, which can be of varying length depending on the user's requirements.

Capabilities

The Mistral-7B-v0.3 model is capable of generating high-quality, coherent text on a wide range of topics. It can be used for tasks such as content generation, language modeling, and text summarization. The extended vocabulary size of 32,768 allows the model to handle more complex and nuanced language compared to its predecessor, the Mistral-7B-v0.2.

What can I use it for?

The Mistral-7B-v0.3 model can be utilized for various applications, such as:

  • Content generation: Generating articles, stories, or blog posts on a wide range of topics.
  • Language modeling: Improving language understanding and generation in conversational AI systems.
  • Text summarization: Condensing long passages of text into concise summaries.

Things to try

To get the most out of the Mistral-7B-v0.3 model, you can try:

  • Experimenting with different prompts and temperature settings to generate diverse and creative text.
  • Incorporating the model into your existing applications or building new applications that leverage its text generation capabilities.
  • Exploring the model's performance on various benchmarks and tasks to understand its strengths and limitations.


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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