cabrita-lora-v0-1
Maintainer: 22h
70
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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
Cabrita is a Portuguese language model that was fine-tuned on a Portuguese translation of the Alpaca dataset. This model is based on the LLaMA-7B architecture and was developed by 22h. Similar models include Sabi-7B, another Portuguese language model, and various Alpaca-based models in different languages and model sizes.
Model inputs and outputs
Cabrita is a text-to-text model, accepting text input and generating text output. The model was fine-tuned on a Portuguese translation of the Alpaca dataset, which consists of a variety of instructions and responses. As a result, the model is well-suited for tasks like question answering, task completion, and open-ended conversation in Portuguese.
Inputs
- Text: The model accepts natural language text in Portuguese as input.
Outputs
- Text: The model generates natural language text in Portuguese as output.
Capabilities
Cabrita is capable of understanding and generating Portuguese text across a variety of domains, including question answering, task completion, and open-ended conversation. The model has been shown to perform well on Portuguese language benchmarks and can be used as a starting point for building Portuguese language applications.
What can I use it for?
Cabrita can be used for a variety of Portuguese language applications, such as:
- Language assistants: Cabrita can be used to build Portuguese-language virtual assistants that can answer questions, complete tasks, and engage in open-ended conversation.
- Content generation: The model can be used to generate Portuguese text for a variety of use cases, such as creative writing, article summarization, or product descriptions.
- Fine-tuning: Cabrita can be fine-tuned on domain-specific data to create specialized Portuguese language models for applications like customer service, medical diagnosis, or legal analysis.
Things to try
One interesting aspect of Cabrita is its ability to generate coherent and contextually relevant responses. For example, you could try prompting the model with a question about a specific topic and see how it responds. You could also try providing the model with a series of instructions and see how it handles task completion. Additionally, you could explore the model's capabilities in open-ended conversation by engaging it in a back-and-forth dialogue.
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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