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README.md

@@ -46,23 +46,24 @@ This repo contains GGUF format model files for [YeungNLP's Firefly Mixtral 8X7B]
 
 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.
 
-### Mixtral GGUF
-
-Support for Mixtral was merged into Llama.cpp on December 13th.
-
-These Mixtral GGUFs are known to work in:
-
-* llama.cpp as of December 13th
-* KoboldCpp 1.52 as later
-* LM Studio 0.2.9 and later
-* llama-cpp-python 0.2.23 and later
-
-Other clients/libraries, not listed above, may not yet work.
+Here is an incomplete list of clients and libraries that are known to support GGUF:
+
+* [llama.cpp](https://github.com/ggerganov/llama.cpp). The source project for GGUF. Offers a CLI and a server option.
+* [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
+* [KoboldCpp](https://github.com/LostRuins/koboldcpp), a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
+* [GPT4All](https://gpt4all.io/index.html), a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
+* [LM Studio](https://lmstudio.ai/), 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](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.
+* [Faraday.dev](https://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](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.
+* [ctransformers](https://github.com/marella/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.
 
 <!-- README_GGUF.md-about-gguf end -->
 <!-- repositories-available start -->
 ## Repositories available
 
+* [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/firefly-mixtral-8x7b-AWQ)
 * [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/firefly-mixtral-8x7b-GPTQ)
 * [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/firefly-mixtral-8x7b-GGUF)
 * [YeungNLP's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/YeungNLP/firefly-mixtral-8x7b)
@@ -82,7 +83,9 @@ Other clients/libraries, not listed above, may not yet work.
 <!-- compatibility_gguf start -->
 ## Compatibility
 
-These Mixtral GGUFs are compatible with llama.cpp from December 13th onwards. Other clients/libraries may not work yet.
+These quantised GGUFv2 files are compatible with llama.cpp from August 27th onwards, as of commit [d0cee0d](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221)
+
+They are also compatible with many third party UIs and libraries - please see the list at the top of this README.
 
 ## Explanation of quantisation methods
 
@@ -198,13 +201,11 @@ For other parameters and how to use them, please refer to [the llama.cpp documen
 
 ## How to run in `text-generation-webui`
 
-Note that text-generation-webui may not yet be compatible with Mixtral GGUFs. Please check compatibility first.
-
 Further instructions can be found in the text-generation-webui documentation, here: [text-generation-webui/docs/04 ‐ Model Tab.md](https://github.com/oobabooga/text-generation-webui/blob/main/docs/04%20%E2%80%90%20Model%20Tab.md#llamacpp).
 
 ## How to run from Python code
 
-You can use GGUF models from Python using the [llama-cpp-python](https://github.com/abetlen/llama-cpp-python) version 0.2.23 and later.
+You can use GGUF models from Python using the [llama-cpp-python](https://github.com/abetlen/llama-cpp-python) or [ctransformers](https://github.com/marella/ctransformers) libraries. Note that at the time of writing (Nov 27th 2023), ctransformers has not been updated for some time and is not compatible with some recent models. Therefore I recommend you use llama-cpp-python.
 
 ### How to load this model in Python code, using llama-cpp-python
 
@@ -273,6 +274,7 @@ llm.create_chat_completion(
 Here are guides on using llama-cpp-python and ctransformers with LangChain:
 
 * [LangChain + llama-cpp-python](https://python.langchain.com/docs/integrations/llms/llamacpp)
+* [LangChain + ctransformers](https://python.langchain.com/docs/integrations/providers/ctransformers)
 
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