mamba-130m
Maintainer: state-spaces
49
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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
The mamba-130m is a text-to-text AI model developed by state-spaces. This model is part of the Mamba family, which includes the mamba-2.8b and mamba-2.8b-slimpj models. The Mamba models are built using the Mamba architecture, as described in the Mamba paper.
Model inputs and outputs
The mamba-130m model is a text-to-text AI model, meaning it takes text as input and generates text as output. The model can be used for a variety of natural language processing tasks, such as translation, summarization, and question-answering.
Inputs
- Text in any language
Outputs
- Text in any language
Capabilities
The mamba-130m model can be used for a variety of text-to-text tasks, such as translation, summarization, and question-answering. The model has been trained on a large corpus of text data and can generate fluent and coherent text in response to a wide range of prompts.
What can I use it for?
The mamba-130m model can be used for a variety of applications, such as:
- Translating text between different languages
- Summarizing long documents or articles
- Answering questions based on provided text
- Generating creative writing or poetry
- Assisting with language learning and education
Things to try
One interesting thing to try with the mamba-130m model is to experiment with different types of prompts and see how the model responds. For example, you could try providing the model with a starting sentence and see how it continues the story. You could also try giving the model a set of instructions or a task and see how it approaches and completes the task.
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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