Update README.md

README.md

@@ -1,3 +1,93 @@
 ---
+library_name: transformers
 license: cc-by-4.0
+language:
+- en
+tags:
+- gguf
+- quantized
+- roleplay
+- imatrix
+- mistral
+- merge
+inference: false
+# base_model:
+# - Epiculous/Fett-uccine-Long-Noodle-7B-120k-Context
+# - Epiculous/Mika-7B
 ---
+
+This repository hosts GGUF-IQ-Imatrix quantizations for **[grimjim/kukulemon-7B](https://huggingface.co/grimjim/kukulemon-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)
+
+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).
+
+**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.
+
+**My waifu image for this card:**
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/65d4cf2693a0a3744a27536c/EO8El-PYPDhqd8LLhGgT1.jpeg)
+
+**Original model information:**
+
+# kukulemon-7B
+
+A merger of two similar models with strong reasoning, hopefully resulting in "dense" encoding of said reasoning, was merged with a model targeting roleplay.
+
+I've tested with ChatML prompts with temperature=1.1 and minP=0.03. The model itself supports Alpaca format prompts. The model claims a context length of 32K, but I've only tested to 8K to date.
+
+This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
+
+## Merge Details
+### Merge Method
+
+This model was merged using the SLERP merge method.
+
+### Models Merged
+
+The following models were included in the merge:
+* [grimjim/kuno-kunoichi-v1-DPO-v2-SLERP-7B](https://huggingface.co/grimjim/kuno-kunoichi-v1-DPO-v2-SLERP-7B)
+* [KatyTheCutie/LemonadeRP-4.5.3](https://huggingface.co/KatyTheCutie/LemonadeRP-4.5.3)
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+slices:
+  - sources:
+      - model: grimjim/kuno-kunoichi-v1-DPO-v2-SLERP-7B
+        layer_range: [0, 32]
+      - model: KatyTheCutie/LemonadeRP-4.5.3
+        layer_range: [0, 32]
+# or, the equivalent models: syntax:
+# models:
+merge_method: slerp
+base_model: KatyTheCutie/LemonadeRP-4.5.3
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5 # fallback for rest of tensors
+dtype: float16
+
+```