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---
license: cc-by-sa-4.0
datasets:
- unalignment/toxic-dpo-v0.2
- athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW-v1-SHUFFLED
- grimulkan/theory-of-mind
- FriezaForce/unranked_theory_of_mind_roleplay
language:
- en
tags:
- not-for-all-audiences
inference: false
---
This repository hosts GGUF-Imatrix quantizations for [ResplendentAI/Paradigm_Shift_7B](https://huggingface.co/ResplendentAI/Paradigm_Shift_7B).
**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]](https://github.com/ggerganov/llama.cpp/discussions/5006) [[2]](https://github.com/ggerganov/llama.cpp/discussions/5263#discussioncomment-8395384)
**Steps:**
```
Base⇢ GGUF(F16)⇢ Imatrix-Data(F16)⇢ GGUF(Imatrix-Quants)
```
Quants:
```python
quantization_options = [
"Q4_K_M", "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.
**This is experimental.**
For imatrix data generation, kalomaze's `groups_merged.txt` with added roleplay chats was used, you can find it [here](https://huggingface.co/Lewdiculous/Datura_7B-GGUF-Imatrix/blob/main/imatrix-with-rp-format-data.txt).
There are more experimental quants in the [**experimental**](https://huggingface.co/Lewdiculous/Paradigm_Shift_7B-GGUF-IQ-Imatrix/tree/main/experimental) folder, these are using [this](https://huggingface.co/Virt-io/Deris-SSS-7B/blob/main/imatrix-test/imatrix-with-rp-Multi-Kaomoji-v1.txt) data for `imatrix`.
**Original card information:**
# Paradigm Shift
A more compliant finetune of Paradigm. I have briefly tested this and it should more readily answer NSFW and difficult queries with fewer refusals. This model will be well suited to RP and question answering.
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