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Model: kainatq/kainaticulous-rp-7b-gguf Source: Original Platform
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kainaticulous-rp-7B-F16.gguf filter=lfs diff=lfs merge=lfs -text
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---
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base_model:
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- mistralai/Mistral-7B-Instruct-v0.2
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- Endevor/InfinityRP-v1-7B
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- mistralai/Mistral-7B-v0.1
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- CalderaAI/Naberius-7B
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- CalderaAI/Hexoteric-7B
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- Endevor/EndlessRP-v3-7B
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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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license: apache-2.0
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pipeline_tag: text-generation
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---
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# merge
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this is a model focused on roleplaying. please dont expect much from it in other areas. it will do its job as roleplaying.
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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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careful it generates nsfw contents. whatever generated by you is your responsibility. ejoy it by roleplaying. cheers ☺️.
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## Merge Details
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### Merge Method
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This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) 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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* [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
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* [Endevor/InfinityRP-v1-7B](https://huggingface.co/Endevor/InfinityRP-v1-7B)
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* [CalderaAI/Naberius-7B](https://huggingface.co/CalderaAI/Naberius-7B)
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* [CalderaAI/Hexoteric-7B](https://huggingface.co/CalderaAI/Hexoteric-7B)
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* [Endevor/EndlessRP-v3-7B](https://huggingface.co/Endevor/EndlessRP-v3-7B)
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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: mistralai/Mistral-7B-v0.1
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#no parameters necessary for base model
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- model: mistralai/Mistral-7B-Instruct-v0.2
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parameters:
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density: 0.6
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weight: 0.25
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- model: Endevor/InfinityRP-v1-7B
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parameters:
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density: 0.6
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weight: 0.25
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- model: Endevor/EndlessRP-v3-7B
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parameters:
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density: 0.6
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weight: 0.25
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- model: CalderaAI/Naberius-7B
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parameters:
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density: 0.6
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weight: 0.25
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- model: CalderaAI/Hexoteric-7B
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parameters:
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density: 0.6
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weight: 0.25
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merge_method: ties
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base_model: mistralai/Mistral-7B-v0.1
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parameters:
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normalize: false
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int8_mask: true
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dtype: float16
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```
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### download
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dowanlod any of one file not all of them.
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### About GGUF
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GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.
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Here is an incomplete list of clients and libraries that are known to support GGUF:
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llama.cpp. The source project for GGUF. Offers a CLI and a server option.
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text-generation-webui, the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
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KoboldCpp, a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
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GPT4All, a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
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LM Studio, an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration. Linux available, in beta as of 27/11/2023.
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LoLLMS Web UI, a great web UI with many interesting and unique features, including a full model library for easy model selection.
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Faraday.dev, an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
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llama-cpp-python, a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
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candle, a Rust ML framework with a focus on performance, including GPU support, and ease of use.
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ctransformers, a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server. Note, as of time of writing (November 27th 2023), ctransformers has not been updated in a long time and does not support many recent models.
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### info
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| Name | Quant method | Bits | Size | Max RAM required | Use case |
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| ---- | ---- | ---- | ---- | ---- | ----- |
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| [Q2_K.gguf)] | Q2_K | 2 | 2.72 GB| 5.22 GB | significant quality loss - not recommended for most purposes |
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| [Q3_K_S.gguf)] | Q3_K_S | 3 | 3.16 GB| 5.66 GB | very small, high quality loss |
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| [Q3_K_M.gguf)] | Q3_K_M | 3 | 3.52 GB| 6.02 GB | very small, high quality loss |
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| [Q3_K_L.gguf)] | Q3_K_L | 3 | 3.82 GB| 6.32 GB | small, substantial quality loss |
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| [Q4_0.gguf)] |Q4_0 | 4 | 4.11 GB| 6.61 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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| [Q4_K_S.gguf)] | Q4_K_S | 4 | 4.14 GB| 6.64 GB | small, greater quality loss |
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| [Q4_K_M.gguf)] | Q4_K_M | 4 | 4.37 GB| 6.87 GB | medium, balanced quality - recommended |
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| [Q5_0.gguf)] | Q5_0 | 5 | 5.00 GB| 7.50 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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| [Q5_K_S.gguf) ]| Q5_K_S | 5 | 5.00 GB| 7.50 GB | large, low quality loss - recommended |
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| [Q5_K_M.gguf) ]| Q5_K_M | 5 | 5.13 GB| 7.63 GB | large, very low quality loss - recommended |
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| [Q6_K.gguf)] | Q6_K | 6 | 5.94 GB| 8.44 GB | very large, extremely low quality loss |
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| [Q8_0.gguf)] | Q8_0 | 8 | 7.70 GB| 10.20 GB | very large, extremely low quality loss - not recommended |
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**Note**: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
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[note this info format is borrowed from @TheBloke (https://huggingface.co/TheBloke) ]
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### citation
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this repo has been used to make the merge.
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```
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@article{goddard2024arcee,
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title={Arcee's MergeKit: A Toolkit for Merging Large Language Models},
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author={Goddard, Charles and Siriwardhana, Shamane and Ehghaghi, Malikeh and Meyers, Luke and Karpukhin, Vlad and Benedict, Brian and McQuade, Mark and Solawetz, Jacob},
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journal={arXiv preprint arXiv:2403.13257},
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year={2024}
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}
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```
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kainaticulous-rp-7B-F16.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:e2a8980babe449abd7bcc8867447f775b465665aa119cce56f6e3ab738121d18
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size 14484733568
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version https://git-lfs.github.com/spec/v1
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oid sha256:20ad5c954ba917db9839de41d86959e1a9829a7e63b63e5a1327d7ba6eb10663
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size 4368440960
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version https://git-lfs.github.com/spec/v1
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oid sha256:20ad5c954ba917db9839de41d86959e1a9829a7e63b63e5a1327d7ba6eb10663
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size 4368440960
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oid sha256:ae3aa7de10fe900d7bfbdc8664c858fccde3858987a046c6ccc943a587e3a5ea
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size 4140375680
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version https://git-lfs.github.com/spec/v1
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oid sha256:18ddbb935bc221c9f7b7cf4b818b0b50e3fcc337162467ea35cdd082b520b855
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size 5131411072
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version https://git-lfs.github.com/spec/v1
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oid sha256:18ddbb935bc221c9f7b7cf4b818b0b50e3fcc337162467ea35cdd082b520b855
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size 5131411072
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