Lewdiculous
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README.md
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This version was initially on the **#experimental** side, but, quality and character card adherence seem to be solid. <br>
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Let's try to make Eris smarter _and cuter_. <br>
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Thanks for the solid work, [@Nitral-AI](https://huggingface.co/Nitral-AI/).
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# Original model information:
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Model outputs are solid in quality, and relevant to given cards.
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---
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license: other
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tags:
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- gguf
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- quantized
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- roleplay
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- multimodal
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- vision
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- sillytavern
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- merge
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- mistral
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---
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This repository hosts GGUF-IQ-Imatrix quants for [Nitral-AI/Eris_PrimeV3.05-Vision-7B](https://huggingface.co/Nitral-AI/Eris_PrimeV3.05-Vision-7B).
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This version was initially on the **#experimental** side, but, quality and character card adherence seem to be solid. <br>
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Let's try to make Eris smarter _and cuter_. <br>
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Thanks for the solid work, [@Nitral-AI](https://huggingface.co/Nitral-AI/).
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This is a #multimodal model that also has vision capabilities. Read the full card information if that is your use case.
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Quants:
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```python
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quantization_options = [
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"Q4_K_M", "Q4_K_S", "IQ4_XS", "Q5_K_M", "Q5_K_S",
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"Q6_K", "Q8_0", "IQ3_M", "IQ3_S", "IQ3_XXS"
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]
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```
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**What does "Imatrix" mean?**
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It stands for **Importance Matrix**, a technique used to improve the quality of quantized models.
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The **Imatrix** is calculated based on calibration data, and it helps determine the importance of different model activations during the quantization process.
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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.
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[[1]](https://github.com/ggerganov/llama.cpp/discussions/5006) [[2]](https://github.com/ggerganov/llama.cpp/discussions/5263#discussioncomment-8395384)
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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). This was just to add a bit more diversity to the data.
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# Vision/multimodal capabilities:
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<details><summary>
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Click here to see how this would work in practice in a roleplay chat.
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</summary>
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![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/65d4cf2693a0a3744a27536c/qGO0nIfZVcyuio5J07sU-.jpeg)
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</details><br>
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<details><summary>
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Click here to see what your SillyTavern Image Captions extension settings should look like.
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</summary>
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![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/65d4cf2693a0a3744a27536c/UpXOnVrzvsMRYeqMaSOaa.jpeg)
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</details><br>
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**If you want to use vision functionality:**
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* Make sure you are using the latest version of [KoboldCpp](https://github.com/LostRuins/koboldcpp).
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To use the multimodal capabilities of this model, such as **vision**, you also need to load the specified **mmproj** file, you can get it [here](https://huggingface.co/cjpais/llava-1.6-mistral-7b-gguf/blob/main/mmproj-model-f16.gguf).
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* You can load the **mmproj** by using the corresponding section in the interface:
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/65d4cf2693a0a3744a27536c/UX6Ubss2EPNAT3SKGMLe0.png)
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* For CLI users, you can load the **mmproj file** by adding the respective flag to your usual command:
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```
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--mmproj your-mmproj-file.gguf
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```
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# Quantization information:
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**Steps performed:**
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```
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Base⇢ GGUF(F16)⇢ Imatrix-Data(F16)⇢ GGUF(Imatrix-Quants)
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```
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*Using the latest llama.cpp at the time.*
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# Original model information:
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Model outputs are solid in quality, and relevant to given cards.
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