vicuna-13B-v1.5-16K-GGUF
Maintainer: TheBloke
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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
The vicuna-13B-v1.5-16K-GGUF model is a large language model created by lmsys and maintained by TheBloke. It is a version of the popular Vicuna model, which was fine-tuned on user-shared conversations from ShareGPT. This GGUF version provides optimized files for CPU and GPU inference using the llama.cpp framework and related tooling.
Similar models maintained by TheBloke include the vicuna-13B-v1.5-16K-GGML and Wizard-Vicuna-13B-Uncensored-GGUF, which offer different quantization methods and tradeoffs between model size, speed, and quality.
Model inputs and outputs
Inputs
- Prompt: The text that is provided to the model as input, which it will use to generate a continuation or response.
Outputs
- Generated text: The text generated by the model in response to the input prompt. This can be a continuation of the prompt, a standalone response, or a combination of the two.
Capabilities
The vicuna-13B-v1.5-16K-GGUF model is a capable text generation model that can be used for a variety of tasks, such as answering questions, generating stories or articles, and engaging in open-ended conversations. It has been fine-tuned to have more natural and coherent conversational abilities compared to the original LLaMA model.
What can I use it for?
The vicuna-13B-v1.5-16K-GGUF model can be used for a wide range of text generation tasks, such as:
- Chatbots and virtual assistants: The model can be used to power conversational AI agents that can engage in natural language interactions.
- Content generation: The model can be used to generate articles, stories, or other types of written content.
- Research and experimentation: The model can be used by researchers and developers to explore the capabilities of large language models and experiment with different fine-tuning and prompting techniques.
Things to try
Some interesting things to try with the vicuna-13B-v1.5-16K-GGUF model include:
- Exploring different prompting techniques: Try using different types of prompts, such as open-ended questions, specific instructions, or creative writing prompts, to see how the model responds.
- Evaluating performance on specific tasks: Use the model to complete tasks like answering questions, summarizing text, or generating creative content, and evaluate its performance.
- Comparing to other models: Compare the outputs of the
vicuna-13B-v1.5-16K-GGUFmodel to those of other similar models, such as the vicuna-13B-v1.5-16K-GGML or Wizard-Vicuna-13B-Uncensored-GGUF, to understand the trade-offs between different quantization methods.
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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