Extended Alpaca (recommended) format, for more information check the main base model card here.
The expected --contextsize this model can handle is 8192.
SillyTavern - TextGen/Samplers.

What does "Imatrix" mean?

It stands for Importance Matrix, a technique used to improve the quality of quantized models. The Imatrix is calculated based on calibration data, and it helps determine the importance of different model activations during the quantization process. The idea is to preserve the most important information during quantization, which can help reduce the loss of model performance, especially when the calibration data is diverse. [1] [2]

For imatrix data generation, kalomaze's groups_merged.txt with added roleplay chats was used, you can find it here. This was just to add a bit more diversity to the data.

Steps:

Base⇢ GGUF(F16)⇢ Imatrix-Data(F16)⇢ GGUF(Imatrix-Quants)

Using the latest llama.cpp at the time.

Quants:

python

    quantization_options = [
        "Q4_K_M", "Q4_K_S", "IQ4_XS", "Q5_K_M", "Q5_K_S",
        "Q6_K", "Q8_0", "IQ3_M", "IQ3_S", "IQ3_XXS"
    ]

If you want anything that's not here or another model, feel free to request.

Original model information:

This model was merged using the passthrough merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

yaml

slices:
  - sources:
      - model: Endevor/InfinityRP-v1-7B
        layer_range: [0, 20]
  - sources:
      - model: l3utterfly/mistral-7b-v0.1-layla-v4
        layer_range: [12, 32]
merge_method: passthrough
dtype: float16

Lewdiculous/Infinitely-Laydiculous-9B-GGUF-IQ-Imatrix

Instruct format, context size, samplers:

Models Merged

Configuration

Lewdiculous/
Infinitely-Laydiculous-9B-GGUF-IQ-Imatrix