Add README.md to repo

README.md

@@ -8,7 +8,6 @@ tags:
 - self-instruct
 - distillation
 - synthetic instruction
-- llamafile
 model_name: Nous Hermes Llama 2 13B
 base_model: NousResearch/Nous-Hermes-Llama2-13b
 inference: false
@@ -32,36 +31,38 @@ quantized_by: TheBloke
 <!-- header start -->
 <!-- 200823 -->
 <div style="width: auto; margin-left: auto; margin-right: auto">
+<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
 </div>
 <div style="display: flex; justify-content: space-between; width: 100%;">
     <div style="display: flex; flex-direction: column; align-items: flex-start;">
-        <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://discord.gg/FwAVVu7eJ4">Chat & support: jartine's Discord server</a></p>
+        <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://discord.gg/theblokeai">Chat & support: TheBloke's Discord server</a></p>
     </div>
     <div style="display: flex; flex-direction: column; align-items: flex-end;">
+        <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
     </div>
 </div>
-<div style="text-align:center; margin-top: 0em; margin-bottom: 0em"><p style="margin-top: 0.25em; margin-bottom: 0em;">jartine's LLM work is generously supported by a grant from <a href="https://mozilla.org">mozilla</a></p></div>
+<div style="text-align:center; margin-top: 0em; margin-bottom: 0em"><p style="margin-top: 0.25em; margin-bottom: 0em;">TheBloke's LLM work is generously supported by a grant from <a href="https://a16z.com">andreessen horowitz (a16z)</a></p></div>
 <hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
 <!-- header end -->
 
-# Nous Hermes Llama 2 13B - llamafile
+# Nous Hermes Llama 2 13B - GGUF
 - Model creator: [NousResearch](https://huggingface.co/NousResearch)
 - Original model: [Nous Hermes Llama 2 13B](https://huggingface.co/NousResearch/Nous-Hermes-Llama2-13b)
 
 <!-- description start -->
 ## Description
 
-This repo contains llamafile format model files for [Nous Research's Nous Hermes Llama 2 13B](https://huggingface.co/NousResearch/Nous-Hermes-Llama2-13b).
+This repo contains GGUF format model files for [Nous Research's Nous Hermes Llama 2 13B](https://huggingface.co/NousResearch/Nous-Hermes-Llama2-13b).
 
-WARNING: This README may contain inaccuracies. It was generated automatically by forking <a href=/TheBloke/Nous-Hermes-Llama2-GGUF>TheBloke/Nous-Hermes-Llama2-GGUF</a> and piping the README through sed. Errors should be reported to jartine, and do not reflect TheBloke. You can support his work on [Patreon](https://www.patreon.com/TheBlokeAI).
-<!-- README_llamafile.md-about-llamafile start -->
-### About llamafile
+<!-- description end -->
+<!-- README_GGUF.md-about-gguf start -->
+### About GGUF
 
-llamafile is a new format introduced by Mozilla Ocho on Nov 20th 2023. It uses Cosmopolitan Libc to turn LLM weights into runnable llama.cpp binaries that run on the stock installs of six OSes for both ARM64 and AMD64. llamafile offers numerous advantages over GGML, such as better tokenisation, and support for special tokens. It is also supports metadata, and is designed to be extensible.
+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. GGUF offers numerous advantages over GGML, such as better tokenisation, and support for special tokens. It is also supports metadata, and is designed to be extensible.
 
-Here is an incomplate list of clients and libraries that are known to support llamafile:
+Here is an incomplate list of clients and libraries that are known to support GGUF:
 
-* [llama.cpp](https://github.com/ggerganov/llama.cpp). The source project for llamafile. Offers a CLI and a server option.
+* [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.
 * [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration.
@@ -71,13 +72,13 @@ Here is an incomplate list of clients and libraries that are known to support ll
 * [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_llamafile.md-about-llamafile end -->
+<!-- README_GGUF.md-about-gguf end -->
 <!-- repositories-available start -->
 ## Repositories available
 
-* [AWQ model(s) for GPU inference.](https://huggingface.co/jartine/Nous-Hermes-Llama2-AWQ)
-* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/jartine/Nous-Hermes-Llama2-GPTQ)
-* [2, 3, 4, 5, 6 and 8-bit llamafile models for CPU+GPU inference](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile)
+* [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-AWQ)
+* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GPTQ)
+* [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF)
 * [NousResearch's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/NousResearch/Nous-Hermes-Llama2-13b)
 <!-- repositories-available end -->
 
@@ -104,10 +105,10 @@ As this model is based on Llama 2, it is also subject to the Meta Llama 2 licens
 
 In the meantime, any questions regarding licensing, and in particular how these two licenses might interact, should be directed to the original model repository: [Nous Research's Nous Hermes Llama 2 13B](https://huggingface.co/NousResearch/Nous-Hermes-Llama2-13b).
 <!-- licensing end -->
-<!-- compatibility_llamafile start -->
+<!-- compatibility_gguf start -->
 ## Compatibility
 
-These quantised llamafilev2 files are compatible with llama.cpp from August 27th onwards, as of commit [d0cee0d36d5be95a0d9088b674dbb27354107221](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221)
+These quantised GGUFv2 files are compatible with llama.cpp from August 27th onwards, as of commit [d0cee0d36d5be95a0d9088b674dbb27354107221](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.
 
@@ -124,34 +125,34 @@ The new methods available are:
 
 Refer to the Provided Files table below to see what files use which methods, and how.
 </details>
-<!-- compatibility_llamafile end -->
+<!-- compatibility_gguf end -->
 
-<!-- README_llamafile.md-provided-files start -->
+<!-- README_GGUF.md-provided-files start -->
 ## Provided files
 
 | Name | Quant method | Bits | Size | Max RAM required | Use case |
 | ---- | ---- | ---- | ---- | ---- | ----- |
-| [nous-hermes-llama2-13b.Q2_K.llamafile](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile/blob/main/nous-hermes-llama2-13b.Q2_K.llamafile) | Q2_K | 2 | 5.43 GB| 7.93 GB | smallest, significant quality loss - not recommended for most purposes |
-| [nous-hermes-llama2-13b.Q3_K_S.llamafile](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile/blob/main/nous-hermes-llama2-13b.Q3_K_S.llamafile) | Q3_K_S | 3 | 5.66 GB| 8.16 GB | very small, high quality loss |
-| [nous-hermes-llama2-13b.Q3_K_M.llamafile](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile/blob/main/nous-hermes-llama2-13b.Q3_K_M.llamafile) | Q3_K_M | 3 | 6.34 GB| 8.84 GB | very small, high quality loss |
-| [nous-hermes-llama2-13b.Q3_K_L.llamafile](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile/blob/main/nous-hermes-llama2-13b.Q3_K_L.llamafile) | Q3_K_L | 3 | 6.93 GB| 9.43 GB | small, substantial quality loss |
-| [nous-hermes-llama2-13b.Q4_0.llamafile](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile/blob/main/nous-hermes-llama2-13b.Q4_0.llamafile) | Q4_0 | 4 | 7.37 GB| 9.87 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
-| [nous-hermes-llama2-13b.Q4_K_S.llamafile](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile/blob/main/nous-hermes-llama2-13b.Q4_K_S.llamafile) | Q4_K_S | 4 | 7.41 GB| 9.91 GB | small, greater quality loss |
-| [nous-hermes-llama2-13b.Q4_K_M.llamafile](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile/blob/main/nous-hermes-llama2-13b.Q4_K_M.llamafile) | Q4_K_M | 4 | 7.87 GB| 10.37 GB | medium, balanced quality - recommended |
-| [nous-hermes-llama2-13b.Q5_0.llamafile](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile/blob/main/nous-hermes-llama2-13b.Q5_0.llamafile) | Q5_0 | 5 | 8.97 GB| 11.47 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
-| [nous-hermes-llama2-13b.Q5_K_S.llamafile](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile/blob/main/nous-hermes-llama2-13b.Q5_K_S.llamafile) | Q5_K_S | 5 | 8.97 GB| 11.47 GB | large, low quality loss - recommended |
-| [nous-hermes-llama2-13b.Q5_K_M.llamafile](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile/blob/main/nous-hermes-llama2-13b.Q5_K_M.llamafile) | Q5_K_M | 5 | 9.23 GB| 11.73 GB | large, very low quality loss - recommended |
-| [nous-hermes-llama2-13b.Q6_K.llamafile](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile/blob/main/nous-hermes-llama2-13b.Q6_K.llamafile) | Q6_K | 6 | 10.68 GB| 13.18 GB | very large, extremely low quality loss |
-| [nous-hermes-llama2-13b.Q8_0.llamafile](https://huggingface.co/jartine/Nous-Hermes-Llama2-llamafile/blob/main/nous-hermes-llama2-13b.Q8_0.llamafile) | Q8_0 | 8 | 13.83 GB| 16.33 GB | very large, extremely low quality loss - not recommended |
+| [nous-hermes-llama2-13b.Q2_K.gguf](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF/blob/main/nous-hermes-llama2-13b.Q2_K.gguf) | Q2_K | 2 | 5.43 GB| 7.93 GB | smallest, significant quality loss - not recommended for most purposes |
+| [nous-hermes-llama2-13b.Q3_K_S.gguf](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF/blob/main/nous-hermes-llama2-13b.Q3_K_S.gguf) | Q3_K_S | 3 | 5.66 GB| 8.16 GB | very small, high quality loss |
+| [nous-hermes-llama2-13b.Q3_K_M.gguf](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF/blob/main/nous-hermes-llama2-13b.Q3_K_M.gguf) | Q3_K_M | 3 | 6.34 GB| 8.84 GB | very small, high quality loss |
+| [nous-hermes-llama2-13b.Q3_K_L.gguf](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF/blob/main/nous-hermes-llama2-13b.Q3_K_L.gguf) | Q3_K_L | 3 | 6.93 GB| 9.43 GB | small, substantial quality loss |
+| [nous-hermes-llama2-13b.Q4_0.gguf](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF/blob/main/nous-hermes-llama2-13b.Q4_0.gguf) | Q4_0 | 4 | 7.37 GB| 9.87 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [nous-hermes-llama2-13b.Q4_K_S.gguf](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF/blob/main/nous-hermes-llama2-13b.Q4_K_S.gguf) | Q4_K_S | 4 | 7.41 GB| 9.91 GB | small, greater quality loss |
+| [nous-hermes-llama2-13b.Q4_K_M.gguf](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF/blob/main/nous-hermes-llama2-13b.Q4_K_M.gguf) | Q4_K_M | 4 | 7.87 GB| 10.37 GB | medium, balanced quality - recommended |
+| [nous-hermes-llama2-13b.Q5_0.gguf](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF/blob/main/nous-hermes-llama2-13b.Q5_0.gguf) | Q5_0 | 5 | 8.97 GB| 11.47 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [nous-hermes-llama2-13b.Q5_K_S.gguf](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF/blob/main/nous-hermes-llama2-13b.Q5_K_S.gguf) | Q5_K_S | 5 | 8.97 GB| 11.47 GB | large, low quality loss - recommended |
+| [nous-hermes-llama2-13b.Q5_K_M.gguf](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF/blob/main/nous-hermes-llama2-13b.Q5_K_M.gguf) | Q5_K_M | 5 | 9.23 GB| 11.73 GB | large, very low quality loss - recommended |
+| [nous-hermes-llama2-13b.Q6_K.gguf](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF/blob/main/nous-hermes-llama2-13b.Q6_K.gguf) | Q6_K | 6 | 10.68 GB| 13.18 GB | very large, extremely low quality loss |
+| [nous-hermes-llama2-13b.Q8_0.gguf](https://huggingface.co/TheBloke/Nous-Hermes-Llama2-GGUF/blob/main/nous-hermes-llama2-13b.Q8_0.gguf) | Q8_0 | 8 | 13.83 GB| 16.33 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.
 
 
 
-<!-- README_llamafile.md-provided-files end -->
+<!-- README_GGUF.md-provided-files end -->
 
-<!-- README_llamafile.md-how-to-download start -->
-## How to download llamafile files
+<!-- README_GGUF.md-how-to-download start -->
+## How to download GGUF files
 
 **Note for manual downloaders:** You almost never want to clone the entire repo! Multiple different quantisation formats are provided, and most users only want to pick and download a single file.
 
@@ -162,7 +163,7 @@ The following clients/libraries will automatically download models for you, prov
 
 ### In `text-generation-webui`
 
-Under Download Model, you can enter the model repo: jartine/Nous-Hermes-Llama2-llamafile and below it, a specific filename to download, such as: nous-hermes-llama2-13b.q4_K_M.llamafile.
+Under Download Model, you can enter the model repo: TheBloke/Nous-Hermes-Llama2-GGUF and below it, a specific filename to download, such as: nous-hermes-llama2-13b.q4_K_M.gguf.
 
 Then click Download.
 
@@ -177,7 +178,7 @@ pip3 install huggingface-hub>=0.17.1
 Then you can download any individual model file to the current directory, at high speed, with a command like this:
 
 ```shell
-huggingface-cli download jartine/Nous-Hermes-Llama2-llamafile nous-hermes-llama2-13b.q4_K_M.llamafile --local-dir . --local-dir-use-symlinks False
+huggingface-cli download TheBloke/Nous-Hermes-Llama2-GGUF nous-hermes-llama2-13b.q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
 ```
 
 <details>
@@ -186,7 +187,7 @@ huggingface-cli download jartine/Nous-Hermes-Llama2-llamafile nous-hermes-llama2
 You can also download multiple files at once with a pattern:
 
 ```shell
-huggingface-cli download jartine/Nous-Hermes-Llama2-llamafile --local-dir . --local-dir-use-symlinks False --include='*Q4_K*llamafile'
+huggingface-cli download TheBloke/Nous-Hermes-Llama2-GGUF --local-dir . --local-dir-use-symlinks False --include='*Q4_K*gguf'
 ```
 
 For more documentation on downloading with `huggingface-cli`, please see: [HF -> Hub Python Library -> Download files -> Download from the CLI](https://huggingface.co/docs/huggingface_hub/guides/download#download-from-the-cli).
@@ -200,25 +201,25 @@ pip3 install hf_transfer
 And set environment variable `HF_HUB_ENABLE_HF_TRANSFER` to `1`:
 
 ```shell
-HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download jartine/Nous-Hermes-Llama2-llamafile nous-hermes-llama2-13b.q4_K_M.llamafile --local-dir . --local-dir-use-symlinks False
+HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download TheBloke/Nous-Hermes-Llama2-GGUF nous-hermes-llama2-13b.q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
 ```
 
 Windows CLI users: Use `set HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1` before running the download command.
 </details>
-<!-- README_llamafile.md-how-to-download end -->
+<!-- README_GGUF.md-how-to-download end -->
 
-<!-- README_llamafile.md-how-to-run start -->
+<!-- README_GGUF.md-how-to-run start -->
 ## Example `llama.cpp` command
 
 Make sure you are using `llama.cpp` from commit [d0cee0d36d5be95a0d9088b674dbb27354107221](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221) or later.
 
 ```shell
-./main -ngl 32 -m nous-hermes-llama2-13b.q4_K_M.llamafile --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{prompt}\n\n### Response:"
+./main -ngl 32 -m nous-hermes-llama2-13b.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{prompt}\n\n### Response:"
 ```
 
 Change `-ngl 32` to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.
 
-Change `-c 4096` to the desired sequence length. For extended sequence models - eg 8K, 16K, 32K - the necessary RoPE scaling parameters are read from the llamafile file and set by llama.cpp automatically.
+Change `-c 4096` to the desired sequence length. For extended sequence models - eg 8K, 16K, 32K - the necessary RoPE scaling parameters are read from the GGUF file and set by llama.cpp automatically.
 
 If you want to have a chat-style conversation, replace the `-p <PROMPT>` argument with `-i -ins`
 
@@ -230,7 +231,7 @@ Further instructions here: [text-generation-webui/docs/llama.cpp.md](https://git
 
 ## How to run from Python code
 
-You can use llamafile models from Python using the [llama-cpp-python](https://github.com/abetlen/llama-cpp-python) or [ctransformers](https://github.com/marella/ctransformers) libraries.
+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.
 
 ### How to load this model from Python using ctransformers
 
@@ -247,13 +248,13 @@ CT_HIPBLAS=1 pip install ctransformers>=0.2.24 --no-binary ctransformers
 CT_METAL=1 pip install ctransformers>=0.2.24 --no-binary ctransformers
 ```
 
-#### Simple example code to load one of these llamafile models
+#### Simple example code to load one of these GGUF models
 
 ```python
 from ctransformers import AutoModelForCausalLM
 
 # Set gpu_layers to the number of layers to offload to GPU. Set to 0 if no GPU acceleration is available on your system.
-llm = AutoModelForCausalLM.from_pretrained("jartine/Nous-Hermes-Llama2-llamafile", model_file="nous-hermes-llama2-13b.q4_K_M.llamafile", model_type="llama", gpu_layers=50)
+llm = AutoModelForCausalLM.from_pretrained("TheBloke/Nous-Hermes-Llama2-GGUF", model_file="nous-hermes-llama2-13b.q4_K_M.gguf", model_type="llama", gpu_layers=50)
 
 print(llm("AI is going to"))
 ```
@@ -265,7 +266,7 @@ Here's guides on using llama-cpp-python or 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)
 
-<!-- README_llamafile.md-how-to-run end -->
+<!-- README_GGUF.md-how-to-run end -->
 
 <!-- footer start -->
 <!-- 200823 -->
@@ -273,23 +274,31 @@ Here's guides on using llama-cpp-python or ctransformers with LangChain:
 
 For further support, and discussions on these models and AI in general, join us at:
 
-[jartine AI's Discord server](https://discord.gg/FwAVVu7eJ4)
+[TheBloke AI's Discord server](https://discord.gg/theblokeai)
 
 ## Thanks, and how to contribute
 
+Thanks to the [chirper.ai](https://chirper.ai) team!
 
+Thanks to Clay from [gpus.llm-utils.org](llm-utils)!
 
 I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.
 
 If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.
 
+Donaters will get priority support on any and all AI/LLM/model questions and requests, access to a private Discord room, plus other benefits.
 
+* Patreon: https://patreon.com/TheBlokeAI
+* Ko-Fi: https://ko-fi.com/TheBlokeAI
 
+**Special thanks to**: Aemon Algiz.
 
+**Patreon special mentions**: Alicia Loh, Stephen Murray, K, Ajan Kanaga, RoA, Magnesian, Deo Leter, Olakabola, Eugene Pentland, zynix, Deep Realms, Raymond Fosdick, Elijah Stavena, Iucharbius, Erik Bjäreholt, Luis Javier Navarrete Lozano, Nicholas, theTransient, John Detwiler, alfie_i, knownsqashed, Mano Prime, Willem Michiel, Enrico Ros, LangChain4j, OG, Michael Dempsey, Pierre Kircher, Pedro Madruga, James Bentley, Thomas Belote, Luke @flexchar, Leonard Tan, Johann-Peter Hartmann, Illia Dulskyi, Fen Risland, Chadd, S_X, Jeff Scroggin, Ken Nordquist, Sean Connelly, Artur Olbinski, Swaroop Kallakuri, Jack West, Ai Maven, David Ziegler, Russ Johnson, transmissions 11, John Villwock, Alps Aficionado, Clay Pascal, Viktor Bowallius, Subspace Studios, Rainer Wilmers, Trenton Dambrowitz, vamX, Michael Levine, 준교 김, Brandon Frisco, Kalila, Trailburnt, Randy H, Talal Aujan, Nathan Dryer, Vadim, 阿明, ReadyPlayerEmma, Tiffany J. Kim, George Stoitzev, Spencer Kim, Jerry Meng, Gabriel Tamborski, Cory Kujawski, Jeffrey Morgan, Spiking Neurons AB, Edmond Seymore, Alexandros Triantafyllidis, Lone Striker, Cap'n Zoog, Nikolai Manek, danny, ya boyyy, Derek Yates, usrbinkat, Mandus, TL, Nathan LeClaire, subjectnull, Imad Khwaja, webtim, Raven Klaugh, Asp the Wyvern, Gabriel Puliatti, Caitlyn Gatomon, Joseph William Delisle, Jonathan Leane, Luke Pendergrass, SuperWojo, Sebastain Graf, Will Dee, Fred von Graf, Andrey, Dan Guido, Daniel P. Andersen, Nitin Borwankar, Elle, Vitor Caleffi, biorpg, jjj, NimbleBox.ai, Pieter, Matthew Berman, terasurfer, Michael Davis, Alex, Stanislav Ovsiannikov
 
 
+Thank you to all my generous patrons and donaters!
 
-And thank you again to mozilla for their generous grant.
+And thank you again to a16z for their generous grant.
 
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