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--- |
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library_name: transformers |
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tags: |
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- mergekit |
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- merge |
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- roleplay |
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- mistral |
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inference: false |
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license: apache-2.0 |
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--- |
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This repository hosts GGUF-IQ-Imatrix quants for [vicgalle/RoleBeagle-11B](https://huggingface.co./vicgalle/RoleBeagle-11B). |
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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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**Steps:** |
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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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```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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## Original model information: |
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# RoleBeagle-11B |
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A DPO-finetune from [vicgalle/CarbonBeagle-11B-truthy](https://huggingface.co./vicgalle/CarbonBeagle-11B-truthy) over a subset of OpenHermesPreferences containting RP conversations. |
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It keeps most of the intelligence from CarbonBeagle-11B, and hopefuly can role-play better. |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_vicgalle__RoleBeagle-11B) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |76.06| |
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|AI2 Reasoning Challenge (25-Shot)|72.35| |
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|HellaSwag (10-Shot) |89.77| |
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|MMLU (5-Shot) |66.35| |
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|TruthfulQA (0-shot) |77.92| |
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|Winogrande (5-shot) |84.06| |
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|GSM8k (5-shot) |65.88| |
