Mistral-Nemo-Instruct-2407-GGUF

Maintainer: second-state

Total Score

62

Last updated 9/4/2024

🛠️

PropertyValue
Run this modelRun on HuggingFace
API specView on HuggingFace
Github linkNo Github link provided
Paper linkNo paper link provided

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Model overview

The Mistral-Nemo-Instruct-2407-GGUF is a large language model created by second-state. It is an instruct fine-tuned version of the Mistral-Nemo-Base-2407 model, trained jointly by Mistral AI and NVIDIA. The model significantly outperforms existing models of similar size, and has a large 128k context window.

Model inputs and outputs

The Mistral-Nemo-Instruct-2407-GGUF model accepts text prompts as input and generates human-like text as output. It uses the mistral-instruct prompt template, which requires the user's message to be wrapped in [INST] and [/INST] tags.

Inputs

  • User message: The user's text prompt, wrapped in [INST] and [/INST] tags.

Outputs

  • Assistant response: The model's generated text response.

Capabilities

The Mistral-Nemo-Instruct-2407-GGUF model is capable of a wide range of natural language tasks, including Q&A, summarization, and open-ended generation. It has strong multilingual capabilities, performing well on benchmarks in several languages.

What can I use it for?

The Mistral-Nemo-Instruct-2407-GGUF model can be used for a variety of applications, such as chatbots, virtual assistants, content generation, and language understanding. Its large context window and instruct fine-tuning make it well-suited for tasks that require longer-form, coherent responses.

Things to try

One interesting thing to try with the Mistral-Nemo-Instruct-2407-GGUF model is to use it for task-oriented dialogue, where you can provide the model with a specific goal or instruction and have it generate a relevant response. The model's instruct fine-tuning allows it to follow instructions and generate content that is tailored to the given task.



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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