alpaca-lora-30b
Maintainer: chansung
50
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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
alpaca-lora-30b is a large language model based on the LLaMA-30B base model, fine-tuned using the Alpaca dataset to create a conversational AI assistant. It was developed by the researcher chansung and is part of the Alpaca-LoRA family of models, which also includes the alpaca-lora-7b and Chinese-Vicuna-lora-13b-belle-and-guanaco models.
Model inputs and outputs
alpaca-lora-30b is a text-to-text model, taking in natural language prompts and generating relevant responses. The model was trained on the Alpaca dataset, a cleaned-up version of the Alpaca dataset up to 04/06/23.
Inputs
- Natural language prompts for the model to respond to
Outputs
- Relevant natural language responses to the input prompts
Capabilities
alpaca-lora-30b can engage in open-ended conversations, answer questions, and complete a variety of language-based tasks. It has been trained to follow instructions and provide informative, coherent responses.
What can I use it for?
alpaca-lora-30b can be used for a wide range of applications, such as chatbots, virtual assistants, and language generation tasks. It could be particularly useful for companies looking to incorporate conversational AI into their products or services.
Things to try
Experiment with different types of prompts to see the range of responses alpaca-lora-30b can generate. You could try asking it follow-up questions, providing it with context about a specific scenario, or challenging it with more complex language tasks.
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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