Update README.md

README.md

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----
-license: apache-2.0
----
+---
+base_model:
+- mistralai/Mistral-7B-Instruct-v0.2
+- Endevor/InfinityRP-v1-7B
+- mistralai/Mistral-7B-v0.1
+- CalderaAI/Naberius-7B
+- CalderaAI/Hexoteric-7B
+- Endevor/EndlessRP-v3-7B
+library_name: transformers
+tags:
+- mergekit
+- merge
+license: apache-2.0
+pipeline_tag: text-generation
+---
+# merge
+this is a model focused on roleplaying. please dont expect much from it in other areas. it will do its job as roleplaying.
+This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
+careful it generates nsfw contents. whatever generated by you is your responsibility. ejoy it by roleplaying. cheers ☺️.
+## Merge Details
+### Merge Method
+
+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.
+
+### Models Merged
+
+The following models were included in the merge:
+* [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
+* [Endevor/InfinityRP-v1-7B](https://huggingface.co/Endevor/InfinityRP-v1-7B)
+* [CalderaAI/Naberius-7B](https://huggingface.co/CalderaAI/Naberius-7B)
+* [CalderaAI/Hexoteric-7B](https://huggingface.co/CalderaAI/Hexoteric-7B)
+* [Endevor/EndlessRP-v3-7B](https://huggingface.co/Endevor/EndlessRP-v3-7B)
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+models:
+  - model: mistralai/Mistral-7B-v0.1
+    #no parameters necessary for base model
+  - model: mistralai/Mistral-7B-Instruct-v0.2
+    parameters:
+      density: 0.6
+      weight: 0.25
+  - model: Endevor/InfinityRP-v1-7B
+    parameters:
+      density: 0.6
+      weight: 0.25
+  - model: Endevor/EndlessRP-v3-7B
+    parameters:
+      density: 0.6
+      weight: 0.25
+  - model: CalderaAI/Naberius-7B
+    parameters:
+      density: 0.6
+      weight: 0.25
+  - model: CalderaAI/Hexoteric-7B
+    parameters:
+      density: 0.6
+      weight: 0.25
+merge_method: ties
+base_model: mistralai/Mistral-7B-v0.1
+parameters:
+  normalize: false
+  int8_mask: true
+dtype: float16
+```
+### download
+dowanlod any of one file not all of them.
+
+### About GGUF
+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.
+
+Here is an incomplete list of clients and libraries that are known to support GGUF:
+
+llama.cpp. The source project for GGUF. Offers a CLI and a server option.
+text-generation-webui, the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
+KoboldCpp, a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
+GPT4All, a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
+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.
+LoLLMS Web UI, a great web UI with many interesting and unique features, including a full model library for easy model selection.
+Faraday.dev, an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
+llama-cpp-python, a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
+candle, a Rust ML framework with a focus on performance, including GPU support, and ease of use.
+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.
+
+### info
+| Name | Quant method | Bits | Size | Max RAM required | Use case |
+| ---- | ---- | ---- | ---- | ---- | ----- |
+| [Q2_K.gguf)] | Q2_K | 2 | 2.72 GB| 5.22 GB | significant quality loss - not recommended for most purposes |
+| [Q3_K_S.gguf)] | Q3_K_S | 3 | 3.16 GB| 5.66 GB | very small, high quality loss |
+| [Q3_K_M.gguf)] | Q3_K_M | 3 | 3.52 GB| 6.02 GB | very small, high quality loss |
+| [Q3_K_L.gguf)] | Q3_K_L | 3 | 3.82 GB| 6.32 GB | small, substantial quality loss |
+| [Q4_0.gguf)]   |Q4_0 | 4 | 4.11 GB| 6.61 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [Q4_K_S.gguf)] | Q4_K_S | 4 | 4.14 GB| 6.64 GB | small, greater quality loss |
+| [Q4_K_M.gguf)] | Q4_K_M | 4 | 4.37 GB| 6.87 GB | medium, balanced quality - recommended |
+| [Q5_0.gguf)] | Q5_0 | 5 | 5.00 GB| 7.50 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [Q5_K_S.gguf) ]| Q5_K_S | 5 | 5.00 GB| 7.50 GB | large, low quality loss - recommended |
+| [Q5_K_M.gguf) ]| Q5_K_M | 5 | 5.13 GB| 7.63 GB | large, very low quality loss - recommended |
+| [Q6_K.gguf)] | Q6_K | 6 | 5.94 GB| 8.44 GB | very large, extremely low quality loss |
+| [Q8_0.gguf)] | Q8_0 | 8 | 7.70 GB| 10.20 GB | very large, extremely low quality loss - not recommended |
+
+**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.
+[note this info format is borrowed from @TheBloke (https://huggingface.co/TheBloke) ]
+### citation
+this repo has been used to make the merge.
+
+```
+@article{goddard2024arcee,
+  title={Arcee's MergeKit: A Toolkit for Merging Large Language Models},
+  author={Goddard, Charles and Siriwardhana, Shamane and Ehghaghi, Malikeh and Meyers, Luke and Karpukhin, Vlad and Benedict, Brian and McQuade, Mark and Solawetz, Jacob},
+  journal={arXiv preprint arXiv:2403.13257},
+  year={2024}
+}
+```