Vicuna-13b has a wide range of use cases for various applications. For chat-based conversation, it can be used to create interactive and engaging chatbots that can effectively respond to user queries and hold meaningful conversations. It can also be utilized in question-answering systems, allowing users to receive accurate and informative responses to their questions. The model's ability to understand natural language makes it suitable for text-based recommender systems, where it can provide personalized recommendations based on user preferences and interests. With its versatility and accessibility through an API, Vicuna-13b opens up possibilities for developing products and services that enhance user interaction and provide valuable information. Potential products using this model could include virtual assistants, customer support chatbots, content recommendation platforms, and personalized search engines.
- Cost per run
- Avg run time
- Nvidia A100 (40GB) GPU
|Flan T5 Xl||$0.0046||98,942|
|Llama 2 7b||$?||5,325|
You can use this area to play around with demo applications that incorporate the Vicuna 13b model. These demos are maintained and hosted externally by third-party creators. If you see an error, message me on Twitter.
Currently, there are no demos available for this model.
Summary of this model and related resources.
|Model Name||Vicuna 13b|
A large language model that's been fine-tuned on ChatGPT interactions
|Model Link||View on Replicate|
|API Spec||View on Replicate|
|Github Link||View on Github|
|Paper Link||View on Arxiv|
How popular is this model, by number of runs? How popular is the creator, by the sum of all their runs?
How much does it cost to run this model? How long, on average, does it take to complete a run?
|Cost per Run||$0.0276|
|Prediction Hardware||Nvidia A100 (40GB) GPU|
|Average Completion Time||12 seconds|