Meta-Llama-3.1-8B-Instruct-abliterated-GGUF
Maintainer: mlabonne
91
⚙️
| 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
Meta-Llama-3.1-8B-Instruct-abliterated is an uncensored version of the Llama 3.1 8B Instruct model created by mlabonne using a technique called "abliteration". This model was developed as a collaboration with FailSpy, who provided the original code and technique. Meta-Llama-3.1-8B-Instruct-abliterated is larger and more capable than the original Llama 2 models, with 8 billion parameters and pretraining on over 15 trillion tokens of data.
Similar models include the Meta-Llama-3-8B-Instruct-GGUF and Meta-Llama-3-120B-Instruct, which are quantized and merged versions of the original Llama 3 models respectively.
Model inputs and outputs
Inputs
- Text data, such as prompts, instructions, or conversation history
Outputs
- Generated text, including responses, continuations, and completions
Capabilities
Meta-Llama-3.1-8B-Instruct-abliterated is a powerful language model capable of a wide range of text generation tasks. It excels at task-oriented dialogue, with the ability to follow instructions and provide helpful, coherent responses. The model also demonstrates strong capabilities in areas like creative writing, open-ended conversation, and code generation.
What can I use it for?
You can use Meta-Llama-3.1-8B-Instruct-abliterated for a variety of applications that involve natural language processing and generation. Some potential use cases include:
- Building interactive chatbots or virtual assistants
- Generating creative writing, stories, or scripts
- Providing code completion and generation assistance
- Summarizing or paraphrasing text
- Engaging in open-ended conversations on a wide range of topics
The model's capabilities make it well-suited for commercial and research applications that require fluent, coherent language generation.
Things to try
One interesting aspect of Meta-Llama-3.1-8B-Instruct-abliterated is its ability to generate text in diverse styles and tones. Try providing the model with different system prompts or persona descriptions to see how it can adapt its language and personality to match the given context. For example, you could try instructing the model to respond as a pirate, a scientist, or a historical figure, and observe how it adjusts its vocabulary, syntax, and tone accordingly.
Another interesting experiment would be to explore the model's capabilities in code generation and programming tasks. Provide the model with programming prompts or problem statements and see how it can generate relevant code snippets or solutions. This could be a useful tool for developers looking to streamline their coding workflow.
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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