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--- |
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license: apache-2.0 |
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language: |
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- en |
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inference: false |
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tags: |
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- roleplay |
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- llama3 |
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- sillytavern |
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--- |
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# #roleplay #sillytavern #llama3 |
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My GGUF-IQ-Imatrix quants for [**nbeerbower/llama-3-Stheno-Mahou-8B**](https://huggingface.co/nbeerbower/llama-3-Stheno-Mahou-8B). |
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"A potential precious hidden gem, will you polish this rough diamond?" |
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This is a merge of two very interesting models, aimed at roleplaying usage. |
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 |
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> [!TIP] |
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> **Personal-support:** <br> |
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> I apologize for disrupting your experience. <br> |
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> Currently I'm working on moving for a better internet provider. <br> |
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> If you **want** and you are **able to**... <br> |
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> You can [**spare some change over here (Ko-fi)**](https://ko-fi.com/Lewdiculous). <br> |
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> |
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> **Author-support:** <br> |
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> You can support the author [**at their own page**](https://huggingface.co/nbeerbower). |
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> [!IMPORTANT] |
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> **Quantization process:** <br> |
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> 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> |
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> Imatrix data was generated from the FP16-GGUF and the final conversions used BF16-GGUF for the quantization process. <br> |
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> This was a bit more disk and compute intensive but hopefully avoided any losses during conversion. <br> |
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> If you noticed any issues let me know in the discussions. |
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> [!NOTE] |
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> **General usage:** <br> |
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> Use the latest version of **KoboldCpp**. <br> |
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> Remember that you can also use `--flashattention` on KoboldCpp now even with non-RTX cards for reduced VRAM usage. <br> |
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> For **8GB VRAM** GPUs, I recommend the **Q4_K_M-imat** quant for up to 12288 context sizes. <br> |
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> For **12GB VRAM** GPUs, the **Q5_K_M-imat** quant will give you a great size/quality balance. <br> |
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> |
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> **Resources:** <br> |
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> 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. |
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> |
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> **Presets:** <br> |
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> Some compatible SillyTavern presets can be found [**here (Virt's Roleplay Presets)**](https://huggingface.co/Virt-io/SillyTavern-Presets), experiment with Llama-3 and ChatML. <br> |
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<!-- > Check [**discussions such as this one**](https://huggingface.co/Virt-io/SillyTavern-Presets/discussions/5#664d6fb87c563d4d95151baa) for other recommendations and samplers. |
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--> |
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## **Original model text information:** |
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# llama-3-Stheno-Mahou-8B |
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). |
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## Merge Details |
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### Merge Method |
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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. |
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### Models Merged |
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The following models were included in the merge: |
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* [flammenai/Mahou-1.1-llama3-8B](https://huggingface.co/flammenai/Mahou-1.1-llama3-8B) |
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* [Sao10K/L3-8B-Stheno-v3.1](https://huggingface.co/Sao10K/L3-8B-Stheno-v3.1) |
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### Configuration |
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The following YAML configuration was used to produce this model: |
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```yaml |
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models: |
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- model: flammenai/Mahou-1.1-llama3-8B |
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- model: Sao10K/L3-8B-Stheno-v3.1 |
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merge_method: model_stock |
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base_model: flammenai/Mahou-1.2-llama3-8B |
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dtype: bfloat16 |
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``` |
