vicuna-7b-v1.1
Maintainer: lmsys
74
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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
vicuna-7b-v1.1 is a chat assistant developed by LMSYS that is fine-tuned from the LLaMA language model. It is trained on around 70,000 conversations collected from ShareGPT, with the goal of improving its conversational abilities. The model is licensed for non-commercial use.
Similar models include the vicuna-13b-v1.1, vicuna-7b-v1.3, vicuna-7b-delta-v0, and vicuna-33b-v1.3. These models differ in their size and training details, but share the same core architecture and approach.
Model inputs and outputs
vicuna-7b-v1.1 is an autoregressive language model that generates text based on its input. The model takes in prompts or partially generated text, and outputs a continuation or response.
Inputs
- Text prompts or partially generated text
Outputs
- Continuation of the input text
- Conversational responses to prompts
Capabilities
vicuna-7b-v1.1 excels at engaging in open-ended conversations, answering questions, and generating relevant and coherent text. It can be used for a variety of language-related tasks, such as chatbots, content generation, and language modeling.
What can I use it for?
The primary use cases for vicuna-7b-v1.1 are research and exploration of large language models and chatbots. Researchers and hobbyists in natural language processing, machine learning, and artificial intelligence can use the model to experiment with conversational AI and push the boundaries of what is possible.
Things to try
You can try using vicuna-7b-v1.1 to engage in open-ended conversations, answer questions, and generate text on a wide range of topics. The model's performance can be further explored and evaluated using the provided leaderboard.
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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