README.md

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## I am still building the structure of these descriptions.

These will contain increasingly more content to help find the best models for a purpose.

# falcon-7b-instruct-grammar - GGUF
- Model creator: [mzbac](https://huggingface.co/mzbac)
- Original model: [falcon-7b-instruct-grammar](https://huggingface.co/mzbac/falcon-7b-instruct-grammar)

`mzbac` provides fine-tuned model variants specialized in Grammar-Correction.

This is their Falcon-Version.

# About GGUF format

`gguf` is the current file format used by the [`ggml`](https://github.com/ggerganov/ggml) library.
A growing list of Software is using it and can therefore use this model.
The core project making use of the ggml library is the [llama.cpp](https://github.com/ggerganov/llama.cpp) project by Georgi Gerganov

# Quantization variants

There is a bunch of quantized files available. How to choose the best for you:

# legacy quants

Q4_0, Q4_1, Q5_0, Q5_1 and Q8 are `legacy` quantization types.
Nevertheless, they are fully supported, as there are several circumstances that cause certain model not to be compatible with the modern K-quants.
Falcon 7B models cannot be quantized to K-quants.

# K-quants

K-quants are based on the idea that the quantization of certain parts affects the quality in different ways. If you quantize certain parts more and others less, you get a more powerful model with the same file size, or a smaller file size and lower memory load with comparable performance.
So, if possible, use K-quants.
With a Q6_K you should find it really hard to find a quality difference to the original model - ask your model two times the same question and you may encounter bigger quality differences.


# Original Model Card:


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<a href="https://github.com/maddes8cht"><img src="/assets/buttons/github-button.jpg" alt="GitHub" /></a>
<a href="https://huggingface.co/maddes8cht"><img src="/assets/buttons/huggingface-button.jpg" alt="HuggingFace" /></a></p>
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