mistral-7b-openorca
Maintainer: nateraw
65
| Property | Value |
|---|---|
| Run this model | Run on Replicate |
| API spec | View on Replicate |
| Github link | View on Github |
| Paper link | No paper link provided |
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Model overview
The mistral-7b-openorca is a large language model developed by Mistral AI and fine-tuned on the OpenOrca dataset. It is a 7 billion parameter model that has been trained to engage in open-ended dialogue and assist with a variety of tasks. This model can be seen as a successor to the Mistral-7B-v0.1 and Dolphin-2.1-Mistral-7B models, which were also based on the Mistral-7B architecture but fine-tuned on different datasets.
Model inputs and outputs
The mistral-7b-openorca model takes a text prompt as input and generates a response as output. The input prompt can be on any topic and the model will attempt to provide a relevant and coherent response. The output is returned as a list of string tokens.
Inputs
- Prompt: The text prompt that the model will use to generate a response.
- Max new tokens: The maximum number of tokens the model should generate as output.
- Temperature: The value used to modulate the next token probabilities.
- Top K: The number of highest probability tokens to consider for generating the output.
- Top P: A probability threshold for generating the output, using nucleus filtering.
- Presence penalty: A penalty applied to tokens based on their previous appearance in the output.
- Frequency penalty: A penalty applied to tokens based on their overall frequency in the output.
- Prompt template: A template used to format the input prompt, with a placeholder for the actual prompt text.
Outputs
- Output: A list of string tokens representing the generated response.
Capabilities
The mistral-7b-openorca model is capable of engaging in open-ended dialogue on a wide range of topics. It can be used for tasks such as answering questions, providing summaries, and generating creative content. The model's performance is likely comparable to similar large language models, such as the Dolphin-2.2.1-Mistral-7B and Mistral-7B-Instruct-v0.2 models, which share the same underlying architecture.
What can I use it for?
The mistral-7b-openorca model can be used for a variety of applications, such as:
- Chatbots and virtual assistants: The model's ability to engage in open-ended dialogue makes it well-suited for building conversational interfaces.
- Content generation: The model can be used to generate creative writing, blog posts, or other types of textual content.
- Question answering: The model can be used to answer questions on a wide range of topics.
- Summarization: The model can be used to summarize long passages of text.
Things to try
One interesting aspect of the mistral-7b-openorca model is its ability to provide step-by-step reasoning for its responses. By using the provided prompt template, users can instruct the model to "Write out your reasoning step-by-step to be sure you get the right answers!" This can be a useful feature for understanding the model's decision-making process and for educational or analytical purposes.
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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