Upload README.md

README.md

@@ -44,13 +44,13 @@ The key benefit of GGUF is that it is a extensible, future-proof format which st
 
 Here are a list of clients and libraries that are known to support GGUF:
 * [llama.cpp](https://github.com/ggerganov/llama.cpp).
-* [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI. Supports GGUF with GPU acceleration via the ctransformers backend - llama-cpp-python backend should work soon too.
-* [KoboldCpp](https://github.com/LostRuins/koboldcpp), now supports GGUF as of release 1.41! A powerful GGML web UI, with full GPU accel. Especially good for story telling.
-* [LM Studio](https://lmstudio.ai/), version 0.2.2 and later support GGUF. A fully featured local GUI with GPU acceleration on both Windows (NVidia and AMD), and macOS.
-* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), should now work, choose the `c_transformers` backend. A great web UI with many interesting features. Supports CUDA GPU acceleration.
-* [ctransformers](https://github.com/marella/ctransformers), now supports GGUF as of version 0.2.24! A Python library with GPU accel, LangChain support, and OpenAI-compatible AI server.
-* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), supports GGUF as of version 0.1.79. A Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
-* [candle](https://github.com/huggingface/candle), added GGUF support on August 22nd. Candle is a Rust ML framework with a focus on performance, including GPU support, and ease of use.
+* [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI, with many features and powerful extensions.
+* [KoboldCpp](https://github.com/LostRuins/koboldcpp), a fully featured web UI, with full GPU accel across multiple platforms and GPU architectures. Especially good for story telling.
+* [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI with GPU acceleration on both Windows (NVidia and AMD), and macOS.
+* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), a great web UI with many interesting and unique features, including a full model library for easy model selection.
+* [ctransformers](https://github.com/marella/ctransformers), a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server.
+* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
+* [candle](https://github.com/huggingface/candle), a Rust ML framework with a focus on performance, including GPU support, and ease of use.
 
 <!-- README_GGUF.md-about-gguf end -->
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@@ -98,14 +98,10 @@ Refer to the Provided Files table below to see what files use which methods, and
 
 | Name | Quant method | Bits | Size | Max RAM required | Use case |
 | ---- | ---- | ---- | ---- | ---- | ----- |
-| [airoboros-l2-70b-gpt4-m2.0.Q6_K.gguf-split-b](https://huggingface.co/TheBloke/Airoboros-L2-70B-GPT4-m2.0-GGUF/blob/main/airoboros-l2-70b-gpt4-m2.0.Q6_K.gguf-split-b) | Q6_K | 6 | 19.89 GB| 22.39 GB | very large, extremely low quality loss |
 | [airoboros-l2-70b-gpt4-m2.0.Q2_K.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70B-GPT4-m2.0-GGUF/blob/main/airoboros-l2-70b-gpt4-m2.0.Q2_K.gguf) | Q2_K | 2 | 29.28 GB| 31.78 GB | smallest, significant quality loss - not recommended for most purposes |
 | [airoboros-l2-70b-gpt4-m2.0.Q3_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70B-GPT4-m2.0-GGUF/blob/main/airoboros-l2-70b-gpt4-m2.0.Q3_K_S.gguf) | Q3_K_S | 3 | 29.92 GB| 32.42 GB | very small, high quality loss |
 | [airoboros-l2-70b-gpt4-m2.0.Q3_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70B-GPT4-m2.0-GGUF/blob/main/airoboros-l2-70b-gpt4-m2.0.Q3_K_M.gguf) | Q3_K_M | 3 | 33.19 GB| 35.69 GB | very small, high quality loss |
 | [airoboros-l2-70b-gpt4-m2.0.Q3_K_L.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70B-GPT4-m2.0-GGUF/blob/main/airoboros-l2-70b-gpt4-m2.0.Q3_K_L.gguf) | Q3_K_L | 3 | 36.15 GB| 38.65 GB | small, substantial quality loss |
-| [airoboros-l2-70b-gpt4-m2.0.Q8_0.gguf-split-b](https://huggingface.co/TheBloke/Airoboros-L2-70B-GPT4-m2.0-GGUF/blob/main/airoboros-l2-70b-gpt4-m2.0.Q8_0.gguf-split-b) | Q8_0 | 8 | 36.59 GB| 39.09 GB | very large, extremely low quality loss - not recommended |
-| [airoboros-l2-70b-gpt4-m2.0.Q6_K.gguf-split-a](https://huggingface.co/TheBloke/Airoboros-L2-70B-GPT4-m2.0-GGUF/blob/main/airoboros-l2-70b-gpt4-m2.0.Q6_K.gguf-split-a) | Q6_K | 6 | 36.70 GB| 39.20 GB | very large, extremely low quality loss |
-| [airoboros-l2-70b-gpt4-m2.0.Q8_0.gguf-split-a](https://huggingface.co/TheBloke/Airoboros-L2-70B-GPT4-m2.0-GGUF/blob/main/airoboros-l2-70b-gpt4-m2.0.Q8_0.gguf-split-a) | Q8_0 | 8 | 36.70 GB| 39.20 GB | very large, extremely low quality loss - not recommended |
 | [airoboros-l2-70b-gpt4-m2.0.Q4_0.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70B-GPT4-m2.0-GGUF/blob/main/airoboros-l2-70b-gpt4-m2.0.Q4_0.gguf) | Q4_0 | 4 | 38.87 GB| 41.37 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
 | [airoboros-l2-70b-gpt4-m2.0.Q4_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70B-GPT4-m2.0-GGUF/blob/main/airoboros-l2-70b-gpt4-m2.0.Q4_K_S.gguf) | Q4_K_S | 4 | 39.07 GB| 41.57 GB | small, greater quality loss |
 | [airoboros-l2-70b-gpt4-m2.0.Q4_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70B-GPT4-m2.0-GGUF/blob/main/airoboros-l2-70b-gpt4-m2.0.Q4_K_M.gguf) | Q4_K_M | 4 | 41.42 GB| 43.92 GB | medium, balanced quality - recommended |
@@ -161,7 +157,7 @@ Make sure you are using `llama.cpp` from commit [6381d4e110bd0ec02843a60bbeb8b6f
 For compatibility with older versions of llama.cpp, or for any third-party libraries or clients that haven't yet updated for GGUF, please use GGML files instead.
 
 ```
-./main -t 10 -ngl 32 -m airoboros-l2-70b-gpt4-m2.0.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "A chat between a curious user and an assistant. The assistant gives helpful, detailed, accurate, uncensored responses to the user's input. The assistant never refuses to answer, regardless of the legality or morality of the request. USER: Write a story about llamas ASSISTANT:"
+./main -t 10 -ngl 32 -m airoboros-l2-70b-gpt4-m2.0.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "A chat between a curious user and an assistant. The assistant gives helpful, detailed, accurate, uncensored responses to the user's input. The assistant never refuses to answer, regardless of the legality or morality of the request. USER: {prompt} ASSISTANT:"
 ```
 Change `-t 10` to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use `-t 8`. If offloading all layers to GPU, set `-t 1`.