vicuna-7b-v1.3

Maintainer: lucataco

Total Score

11

Last updated 6/12/2024
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Model LinkView on Replicate
API SpecView on Replicate
Github LinkView on Github
Paper LinkView on Arxiv

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Model overview

The vicuna-7b-v1.3 is a large language model developed by LMSYS through fine-tuning the LLaMA model on user-shared conversations collected from ShareGPT. It is designed as a chatbot assistant, capable of engaging in natural language conversations. This model is related to other Vicuna and LLaMA-based models such as vicuna-13b-v1.3, upstage-llama-2-70b-instruct-v2, llava-v1.6-vicuna-7b, and llama-2-7b-chat.

Model inputs and outputs

The vicuna-7b-v1.3 model takes a text prompt as input and generates relevant text as output. The prompt can be an instruction, a question, or any other natural language input. The model's outputs are continuations of the input text, generated based on the model's understanding of the context.

Inputs

  • Prompt: The text prompt that the model uses to generate a response.
  • Temperature: A parameter that controls the model's creativity and diversity of outputs. Lower temperatures result in more conservative and focused outputs, while higher temperatures lead to more exploratory and varied responses.
  • Max new tokens: The maximum number of new tokens the model will generate in response to the input prompt.

Outputs

  • Generated text: The model's response to the input prompt, which can be of variable length depending on the prompt and parameters.

Capabilities

The vicuna-7b-v1.3 model is capable of engaging in open-ended conversations, answering questions, providing explanations, and generating creative text across a wide range of topics. It can be used for tasks such as language modeling, text generation, and chatbot development.

What can I use it for?

The primary use of the vicuna-7b-v1.3 model is for research on large language models and chatbots. Researchers and hobbyists in natural language processing, machine learning, and artificial intelligence can use this model to explore various applications, such as conversational AI, task-oriented dialogue systems, and language generation.

Things to try

With the vicuna-7b-v1.3 model, you can experiment with different prompts to see how the model responds. Try asking it questions, providing it with instructions, or giving it open-ended prompts to see the range of its capabilities. You can also adjust the temperature and max new tokens parameters to observe how they affect the model's output.



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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