Update README.md

README.md

@@ -1,9 +1,82 @@
 ---
 license: apache-2.0
+language:
+- en
+inference: false
+tags:
+- roleplay
+- llama3
+- sillytavern
 ---
-Testing quants for [**nbeerbower/llama-3-Stheno-Mahou-8B**](https://huggingface.co/nbeerbower/llama-3-Stheno-Mahou-8B).
 
-Once confirmed working and performace is evaluated this will converted to a proper card, with the appropriate waifu image to show it's stable.
+# #roleplay #sillytavern #llama3
 
-For some reason uploads right now for me are **terribly slow**, something might be broken in the platform. <br>
-The other quants will come when it's working again.
+My GGUF-IQ-Imatrix quants for [**nbeerbower/llama-3-Stheno-Mahou-8B**](https://huggingface.co/nbeerbower/llama-3-Stheno-Mahou-8B).
+
+"A potential precious hidden gem, will you polish this rough diamond?"
+
+> [!IMPORTANT]
+> **Quantization process:** <br>
+> For future reference, these quants have been done after the fixes from [**#6920**](https://github.com/ggerganov/llama.cpp/pull/6920) have been merged. <br>
+> Imatrix data was generated from the FP16-GGUF and the final conversions used BF16-GGUF for the quantization process. <br>
+> This was a bit more disk and compute intensive but hopefully avoided any losses during conversion. <br>
+> If you noticed any issues let me know in the discussions.
+
+> [!NOTE]
+> **General usage:** <br>
+> Use the latest version of **KoboldCpp**. <br>
+> Remember that you can also use `--flashattention` on KoboldCpp now even with non-RTX cards for reduced VRAM usage. <br>
+> For **8GB VRAM** GPUs, I recommend the **Q4_K_M-imat** quant for up to 12288 context sizes. <br>
+> For **12GB VRAM** GPUs, the **Q5_K_M-imat** quant will give you a great size/quality balance. <br>
+>
+> **Resources:** <br>
+> You can find out more about how each quant stacks up against each other and their types [**here**](https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9) and [**here**](https://rentry.org/llama-cpp-quants-or-fine-ill-do-it-myself-then-pt-2), respectively.
+> 
+> **Presets:** <br>
+> Some compatible SillyTavern presets can be found [**here (Virt's Roleplay Presets)**](https://huggingface.co/Virt-io/SillyTavern-Presets). <br>
+<!-- > Check [**discussions such as this one**](https://huggingface.co/Virt-io/SillyTavern-Presets/discussions/5#664d6fb87c563d4d95151baa) for other recommendations and samplers.
+-->
+
+> [!TIP]
+> **Personal-support:** <br>
+> I apologize for disrupting your experience. <br>
+> Currently I'm working on moving for a better internet provider. <br>
+> If you **want** and you are **able to**... <br>
+> You can [**spare some change over here (Ko-fi)**](https://ko-fi.com/Lewdiculous). <br>
+>
+> **Author-support:** <br>
+> You can support the author [**at their own page**](https://huggingface.co/Nitral-AI).
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65d4cf2693a0a3744a27536c/mhMDEV-VH2cbHvThdZA0T.png)
+
+## **Original model text information:**
+
+# llama-3-Stheno-Mahou-8B
+
+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 [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [flammenai/Mahou-1.2-llama3-8B](https://huggingface.co/flammenai/Mahou-1.2-llama3-8B) as a base.
+
+### Models Merged
+
+The following models were included in the merge:
+* [flammenai/Mahou-1.1-llama3-8B](https://huggingface.co/flammenai/Mahou-1.1-llama3-8B)
+* [Sao10K/L3-8B-Stheno-v3.1](https://huggingface.co/Sao10K/L3-8B-Stheno-v3.1)
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+models:
+  - model: flammenai/Mahou-1.1-llama3-8B
+  - model: Sao10K/L3-8B-Stheno-v3.1
+merge_method: model_stock
+base_model: flammenai/Mahou-1.2-llama3-8B
+dtype: bfloat16
+
+
+```