WizardLM-7B-uncensored-GGML
Maintainer: TheBloke
122
🏷️
| 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 WizardLM-7B-uncensored-GGML is a large language model created by Eric Hartford and maintained by TheBloke. It is an "uncensored" version of the WizardLM-7B model, meaning it has had certain alignment and moralizing responses removed from the training data. This is intended to create a more flexible model that allows the user to add their own alignment or other biases as needed, rather than having them baked into the model itself.
The model is available in a variety of quantized GGML formats, which allow for efficient inference on both CPUs and GPUs using tools like llama.cpp and compatible UIs. TheBloke has also provided similar uncensored models at larger scales, including the WizardLM-13B-Uncensored-GGML and WizardLM-30B-Uncensored-GGML.
Model inputs and outputs
Inputs
- Prompt: The input text that the model will use to generate a response.
Outputs
- Generated text: The model's response to the provided prompt, which can be of variable length.
Capabilities
The WizardLM-7B-uncensored-GGML model is a powerful language generation tool that can be used for a variety of tasks, such as writing stories, answering questions, or engaging in open-ended conversations. Its "uncensored" nature means it does not have the same built-in ethical constraints as some other language models, allowing for more flexible and wide-ranging outputs.
What can I use it for?
This model could be useful for creative writing projects, chatbots, virtual assistants, and other applications where an open-ended, versatile language generation model is needed. However, its uncensored nature also means it requires careful consideration and responsibility when using, as the outputs may contain content that some find objectionable. It's important to establish appropriate guardrails and moderation when deploying this model in real-world applications.
Things to try
One interesting aspect of the WizardLM-7B-uncensored-GGML model is its ability to generate highly detailed and imaginative stories. You could try providing it with a simple prompt about a fantasy world or character, and see what kind of elaborate narrative it comes up with. Another interesting experiment would be to fine-tune the model on a specific dataset or task, and observe how its outputs change compared to the base uncensored model.
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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