Update README.md

README.md

@@ -66,7 +66,7 @@ These files are GGML format model files for [OpenAccess AI Collective's Minotaur
 GGML files are for CPU + GPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp) and libraries and UIs which support this format, such as:
 * [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
 * [KoboldCpp](https://github.com/LostRuins/koboldcpp)
-* [ParisNeo/GPT4All-UI](https://github.com/ParisNeo/gpt4all-ui)
+* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui)
 * [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)
 * [ctransformers](https://github.com/marella/ctransformers)
 
@@ -78,7 +78,7 @@ GGML files are for CPU + GPU inference using [llama.cpp](https://github.com/gger
 
 ## A note regarding context length
 
-it is currently untested as to whether the 8K context is compatible with available clients such as text-generation-webui, KoboldCpp, etc.
+it is currently untested as to whether the 8K context is compatible with available clients/libraries such as KoboldCpp, ctransformers, etc.
 
 If you have feedback on this, please let me know.
 
@@ -87,33 +87,25 @@ If you have feedback on this, please let me know.
 USER: <prompt>
 ASSISTANT:
 ```
-
 <!-- compatibility_ggml start -->
-## Compatibility
-
-### Original llama.cpp quant methods: `q4_0, q4_1, q5_0, q5_1, q8_0`
-
-I have quantized these 'original' quantisation methods using an older version of llama.cpp so that they remain compatible with llama.cpp as of May 19th, commit `2d5db48`.
-
-These are guaranteed to be compatbile with any UIs, tools and libraries released since late May.
+## Compatibilty
 
-### New k-quant methods: `q2_K, q3_K_S, q3_K_M, q3_K_L, q4_K_S, q4_K_M, q5_K_S, q6_K`
+These files are **not** compatible with llama.cpp.
 
-These new quantisation methods are compatible with llama.cpp as of June 6th, commit `2d43387`.
+Currently they can be used with:
+* KoboldCpp, a powerful inference engine based on llama.cpp, with good UI: [KoboldCpp](https://github.com/LostRuins/koboldcpp)
+* The ctransformers Python library, which includes LangChain support: [ctransformers](https://github.com/marella/ctransformers)
+* The LoLLMS Web UI which uses ctransformers: [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui)
+* [rustformers' llm](https://github.com/rustformers/llm)
+* The example `starcoder` binary provided with [ggml](https://github.com/ggerganov/ggml)
 
-They are now also compatible with recent releases of text-generation-webui, KoboldCpp, llama-cpp-python and ctransformers. Other tools and libraries may or may not be compatible - check their documentation if in doubt.
+As other options become available I will endeavour to update them here (do let me know in the Community tab if I've missed something!)
 
-## Explanation of the new k-quant methods
+## Tutorial for using LoLLMS Web UI
 
-The new methods available are:
-* GGML_TYPE_Q2_K - "type-1" 2-bit quantization in super-blocks containing 16 blocks, each block having 16 weight. Block scales and mins are quantized with 4 bits. This ends up effectively using 2.5625 bits per weight (bpw)
-* GGML_TYPE_Q3_K - "type-0" 3-bit quantization in super-blocks containing 16 blocks, each block having 16 weights. Scales are quantized with 6 bits. This end up using 3.4375 bpw.
-* GGML_TYPE_Q4_K - "type-1" 4-bit quantization in super-blocks containing 8 blocks, each block having 32 weights. Scales and mins are quantized with 6 bits. This ends up using 4.5 bpw.
-* GGML_TYPE_Q5_K - "type-1" 5-bit quantization. Same super-block structure as GGML_TYPE_Q4_K resulting in 5.5 bpw
-* GGML_TYPE_Q6_K - "type-0" 6-bit quantization. Super-blocks with 16 blocks, each block having 16 weights. Scales are quantized with 8 bits. This ends up using 6.5625 bpw
-* GGML_TYPE_Q8_K - "type-0" 8-bit quantization. Only used for quantizing intermediate results. The difference to the existing Q8_0 is that the block size is 256. All 2-6 bit dot products are implemented for this quantization type.
+* [Text tutorial, written by **Lucas3DCG**](https://huggingface.co/TheBloke/MPT-7B-Storywriter-GGML/discussions/2#6475d914e9b57ce0caa68888)
+* [Video tutorial, by LoLLMS Web UI's author **ParisNeo**](https://www.youtube.com/watch?v=ds_U0TDzbzI)
 
-Refer to the Provided Files table below to see what files use which methods, and how.
 <!-- compatibility_ggml end -->
 
 ## Provided files
@@ -125,26 +117,8 @@ Refer to the Provided Files table below to see what files use which methods, and
 | minotaur-15b.ggmlv3.q5_1.bin | q5_1 | 5 | 14.26 GB | 16.76 GB | Original llama.cpp quant method, 5-bit. Even higher accuracy, resource usage and slower inference. |
 | minotaur-15b.ggmlv3.q8_0.bin | q8_0 | 8 | 20.11 GB | 22.61 GB | Original llama.cpp quant method, 8-bit. Almost indistinguishable from float16. High resource use and slow. Not recommended for most users. |
 
-
 **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.
 
-## How to run in `llama.cpp`
-
-I use the following command line; adjust for your tastes and needs:
-
-```
-./main -t 10 -ngl 32 -m minotaur-15b.ggmlv3.q5_0.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "### Instruction: Write a story about llamas\n### Response:"
-```
-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`.
-
-Change `-ngl 32` to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.
-
-If you want to have a chat-style conversation, replace the `-p <PROMPT>` argument with `-i -ins`
-
-## How to run in `text-generation-webui`
-
-Further instructions here: [text-generation-webui/docs/llama.cpp-models.md](https://github.com/oobabooga/text-generation-webui/blob/main/docs/llama.cpp-models.md).
-
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