rename : ggerganov -> ggml-org (#3005)

README.md

@@ -2,12 +2,12 @@
 
 ![whisper.cpp](https://user-images.githubusercontent.com/1991296/235238348-05d0f6a4-da44-4900-a1de-d0707e75b763.jpeg)
 
-[![Actions Status](https://github.com/ggerganov/whisper.cpp/workflows/CI/badge.svg)](https://github.com/ggerganov/whisper.cpp/actions)
+[![Actions Status](https://github.com/ggml-org/whisper.cpp/workflows/CI/badge.svg)](https://github.com/ggml-org/whisper.cpp/actions)
 [![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)
 [![Conan Center](https://shields.io/conan/v/whisper-cpp)](https://conan.io/center/whisper-cpp)
 [![npm](https://img.shields.io/npm/v/whisper.cpp.svg)](https://www.npmjs.com/package/whisper.cpp/)
 
-Stable: [v1.7.5](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.7.5) / [Roadmap](https://github.com/users/ggerganov/projects/16/)
+Stable: [v1.7.5](https://github.com/ggml-org/whisper.cpp/releases/tag/v1.7.5) / [Roadmap](https://github.com/orgs/ggml-org/projects/4/)
 
 High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisper) automatic speech recognition (ASR) model:
 
@@ -23,7 +23,7 @@ High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisp
 - [Efficient GPU support for NVIDIA](#nvidia-gpu-support)
 - [OpenVINO Support](#openvino-support)
 - [Ascend NPU Support](#ascend-npu-support)
-- [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/include/whisper.h)
+- [C-style API](https://github.com/ggml-org/whisper.cpp/blob/master/include/whisper.h)
 
 Supported platforms:
 
@@ -31,14 +31,14 @@ Supported platforms:
 - [x] [iOS](examples/whisper.objc)
 - [x] [Android](examples/whisper.android)
 - [x] [Java](bindings/java/README.md)
-- [x] Linux / [FreeBSD](https://github.com/ggerganov/whisper.cpp/issues/56#issuecomment-1350920264)
+- [x] Linux / [FreeBSD](https://github.com/ggml-org/whisper.cpp/issues/56#issuecomment-1350920264)
 - [x] [WebAssembly](examples/whisper.wasm)
-- [x] Windows ([MSVC](https://github.com/ggerganov/whisper.cpp/blob/master/.github/workflows/build.yml#L117-L144) and [MinGW](https://github.com/ggerganov/whisper.cpp/issues/168)]
-- [x] [Raspberry Pi](https://github.com/ggerganov/whisper.cpp/discussions/166)
-- [x] [Docker](https://github.com/ggerganov/whisper.cpp/pkgs/container/whisper.cpp)
+- [x] Windows ([MSVC](https://github.com/ggml-org/whisper.cpp/blob/master/.github/workflows/build.yml#L117-L144) and [MinGW](https://github.com/ggml-org/whisper.cpp/issues/168)]
+- [x] [Raspberry Pi](https://github.com/ggml-org/whisper.cpp/discussions/166)
+- [x] [Docker](https://github.com/ggml-org/whisper.cpp/pkgs/container/whisper.cpp)
 
 The entire high-level implementation of the model is contained in [whisper.h](include/whisper.h) and [whisper.cpp](src/whisper.cpp).
-The rest of the code is part of the [`ggml`](https://github.com/ggerganov/ggml) machine learning library.
+The rest of the code is part of the [`ggml`](https://github.com/ggml-org/ggml) machine learning library.
 
 Having such a lightweight implementation of the model allows to easily integrate it in different platforms and applications.
 As an example, here is a video of running the model on an iPhone 13 device - fully offline, on-device: [whisper.objc](examples/whisper.objc)
@@ -51,14 +51,14 @@ https://user-images.githubusercontent.com/1991296/204038393-2f846eae-c255-4099-a
 
 On Apple Silicon, the inference runs fully on the GPU via Metal:
 
-https://github.com/ggerganov/whisper.cpp/assets/1991296/c82e8f86-60dc-49f2-b048-d2fdbd6b5225
+https://github.com/ggml-org/whisper.cpp/assets/1991296/c82e8f86-60dc-49f2-b048-d2fdbd6b5225
 
 ## Quick start
 
 First clone the repository:
 
 ```bash
-git clone https://github.com/ggerganov/whisper.cpp.git
+git clone https://github.com/ggml-org/whisper.cpp.git
 ```
 
 Navigate into the directory:
@@ -222,7 +222,7 @@ speed-up - more than x3 faster compared with CPU-only execution. Here are the in
   The first run on a device is slow, since the ANE service compiles the Core ML model to some device-specific format.
   Next runs are faster.
 
-For more information about the Core ML implementation please refer to PR [#566](https://github.com/ggerganov/whisper.cpp/pull/566).
+For more information about the Core ML implementation please refer to PR [#566](https://github.com/ggml-org/whisper.cpp/pull/566).
 
 ## OpenVINO support
 
@@ -307,7 +307,7 @@ This can result in significant speedup in encoder performance. Here are the inst
   The first time run on an OpenVINO device is slow, since the OpenVINO framework will compile the IR (Intermediate Representation) model to a device-specific 'blob'. This device-specific blob will get
   cached for the next run.
 
-For more information about the OpenVINO implementation please refer to PR [#1037](https://github.com/ggerganov/whisper.cpp/pull/1037).
+For more information about the OpenVINO implementation please refer to PR [#1037](https://github.com/ggml-org/whisper.cpp/pull/1037).
 
 ## NVIDIA GPU support
 
@@ -385,8 +385,8 @@ Run the inference examples as usual, for example:
 
 We have two Docker images available for this project:
 
-1. `ghcr.io/ggerganov/whisper.cpp:main`: This image includes the main executable file as well as `curl` and `ffmpeg`. (platforms: `linux/amd64`, `linux/arm64`)
-2. `ghcr.io/ggerganov/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`)
+1. `ghcr.io/ggml-org/whisper.cpp:main`: This image includes the main executable file as well as `curl` and `ffmpeg`. (platforms: `linux/amd64`, `linux/arm64`)
+2. `ghcr.io/ggml-org/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`)
 
 ### Usage
 
@@ -424,8 +424,8 @@ For detailed instructions on how to use Conan, please refer to the [Conan docume
 
 This is a naive example of performing real-time inference on audio from your microphone.
 The [stream](examples/stream) tool samples the audio every half a second and runs the transcription continuously.
-More info is available in [issue #10](https://github.com/ggerganov/whisper.cpp/issues/10). 
-You will need to have [sdl2](https://wiki.libsdl.org/SDL2/Installation) installed for it to work properly. 
+More info is available in [issue #10](https://github.com/ggml-org/whisper.cpp/issues/10).
+You will need to have [sdl2](https://wiki.libsdl.org/SDL2/Installation) installed for it to work properly.
 
 ```bash
 cmake -B build -DWHISPER_SDL2=ON
@@ -513,7 +513,7 @@ main: processing './samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 pr
 
 ## Speaker segmentation via tinydiarize (experimental)
 
-More information about this approach is available here: https://github.com/ggerganov/whisper.cpp/pull/1058
+More information about this approach is available here: https://github.com/ggml-org/whisper.cpp/pull/1058
 
 Sample usage:
 
@@ -577,7 +577,7 @@ https://user-images.githubusercontent.com/1991296/199337538-b7b0c7a3-2753-4a88-a
 
 ## Video comparison of different models
 
-Use the [scripts/bench-wts.sh](https://github.com/ggerganov/whisper.cpp/blob/master/scripts/bench-wts.sh) script to generate a video in the following format:
+Use the [scripts/bench-wts.sh](https://github.com/ggml-org/whisper.cpp/blob/master/scripts/bench-wts.sh) script to generate a video in the following format:
 
 ```bash
 ./scripts/bench-wts.sh samples/jfk.wav
@@ -594,7 +594,7 @@ In order to have an objective comparison of the performance of the inference acr
 use the [whisper-bench](examples/bench) tool. The tool simply runs the Encoder part of the model and prints how much time it
 took to execute it. The results are summarized in the following Github issue:
 
-[Benchmark results](https://github.com/ggerganov/whisper.cpp/issues/89)
+[Benchmark results](https://github.com/ggml-org/whisper.cpp/issues/89)
 
 Additionally a script to run whisper.cpp with different models and audio files is provided [bench.py](scripts/bench.py).
 
@@ -621,25 +621,24 @@ You can download the converted models using the [models/download-ggml-model.sh](
 or manually from here:
 
 - https://huggingface.co/ggerganov/whisper.cpp
-- https://ggml.ggerganov.com
 
 For more details, see the conversion script [models/convert-pt-to-ggml.py](models/convert-pt-to-ggml.py) or [models/README.md](models/README.md).
 
-## [Bindings](https://github.com/ggerganov/whisper.cpp/discussions/categories/bindings)
+## [Bindings](https://github.com/ggml-org/whisper.cpp/discussions/categories/bindings)
 
-- [x] Rust: [tazz4843/whisper-rs](https://github.com/tazz4843/whisper-rs) | [#310](https://github.com/ggerganov/whisper.cpp/discussions/310)
-- [x] JavaScript: [bindings/javascript](bindings/javascript) | [#309](https://github.com/ggerganov/whisper.cpp/discussions/309)
+- [x] Rust: [tazz4843/whisper-rs](https://github.com/tazz4843/whisper-rs) | [#310](https://github.com/ggml-org/whisper.cpp/discussions/310)
+- [x] JavaScript: [bindings/javascript](bindings/javascript) | [#309](https://github.com/ggml-org/whisper.cpp/discussions/309)
   - React Native (iOS / Android): [whisper.rn](https://github.com/mybigday/whisper.rn)
-- [x] Go: [bindings/go](bindings/go) | [#312](https://github.com/ggerganov/whisper.cpp/discussions/312)
+- [x] Go: [bindings/go](bindings/go) | [#312](https://github.com/ggml-org/whisper.cpp/discussions/312)
 - [x] Java:
   - [GiviMAD/whisper-jni](https://github.com/GiviMAD/whisper-jni)
-- [x] Ruby: [bindings/ruby](bindings/ruby) | [#507](https://github.com/ggerganov/whisper.cpp/discussions/507)
-- [x] Objective-C / Swift: [ggerganov/whisper.spm](https://github.com/ggerganov/whisper.spm) | [#313](https://github.com/ggerganov/whisper.cpp/discussions/313)
+- [x] Ruby: [bindings/ruby](bindings/ruby) | [#507](https://github.com/ggml-org/whisper.cpp/discussions/507)
+- [x] Objective-C / Swift: [ggml-org/whisper.spm](https://github.com/ggml-org/whisper.spm) | [#313](https://github.com/ggml-org/whisper.cpp/discussions/313)
   - [exPHAT/SwiftWhisper](https://github.com/exPHAT/SwiftWhisper)
-- [x] .NET: | [#422](https://github.com/ggerganov/whisper.cpp/discussions/422)
+- [x] .NET: | [#422](https://github.com/ggml-org/whisper.cpp/discussions/422)
   - [sandrohanea/whisper.net](https://github.com/sandrohanea/whisper.net)
   - [NickDarvey/whisper](https://github.com/NickDarvey/whisper)
-- [x] Python: | [#9](https://github.com/ggerganov/whisper.cpp/issues/9)
+- [x] Python: | [#9](https://github.com/ggml-org/whisper.cpp/issues/9)
   - [stlukey/whispercpp.py](https://github.com/stlukey/whispercpp.py) (Cython)
   - [AIWintermuteAI/whispercpp](https://github.com/AIWintermuteAI/whispercpp) (Updated fork of aarnphm/whispercpp)
   - [aarnphm/whispercpp](https://github.com/aarnphm/whispercpp) (Pybind11)
@@ -667,7 +666,7 @@ let package = Package(
             ]),
         .binaryTarget(
             name: "WhisperFramework",
-            url: "https://github.com/ggerganov/whisper.cpp/releases/download/v1.7.5/whisper-v1.7.5-xcframework.zip",
+            url: "https://github.com/ggml-org/whisper.cpp/releases/download/v1.7.5/whisper-v1.7.5-xcframework.zip",
             checksum: "c7faeb328620d6012e130f3d705c51a6ea6c995605f2df50f6e1ad68c59c6c4a"
         )
     ]
@@ -692,13 +691,13 @@ Some of the examples are even ported to run in the browser using WebAssembly. Ch
 | [whisper.android](examples/whisper.android)         |                                       | Android mobile application using whisper.cpp                                                                                    |
 | [whisper.nvim](examples/whisper.nvim)               |                                       | Speech-to-text plugin for Neovim                                                                                                |
 | [generate-karaoke.sh](examples/generate-karaoke.sh) |                                       | Helper script to easily [generate a karaoke video](https://youtu.be/uj7hVta4blM) of raw audio capture                           |
-| [livestream.sh](examples/livestream.sh)             |                                       | [Livestream audio transcription](https://github.com/ggerganov/whisper.cpp/issues/185)                                           |
+| [livestream.sh](examples/livestream.sh)             |                                       | [Livestream audio transcription](https://github.com/ggml-org/whisper.cpp/issues/185)                                            |
 | [yt-wsp.sh](examples/yt-wsp.sh)                     |                                       | Download + transcribe and/or translate any VOD [(original)](https://gist.github.com/DaniruKun/96f763ec1a037cc92fe1a059b643b818) |
 | [wchess](examples/wchess)                           | [wchess.wasm](examples/wchess)        | Voice-controlled chess                                                                                                          |
 
-## [Discussions](https://github.com/ggerganov/whisper.cpp/discussions)
+## [Discussions](https://github.com/ggml-org/whisper.cpp/discussions)
 
 If you have any kind of feedback about this project feel free to use the Discussions section and open a new topic.
-You can use the [Show and tell](https://github.com/ggerganov/whisper.cpp/discussions/categories/show-and-tell) category
+You can use the [Show and tell](https://github.com/ggml-org/whisper.cpp/discussions/categories/show-and-tell) category
 to share your own projects that use `whisper.cpp`. If you have a question, make sure to check the
-[Frequently asked questions (#126)](https://github.com/ggerganov/whisper.cpp/discussions/126) discussion.
+[Frequently asked questions (#126)](https://github.com/ggml-org/whisper.cpp/discussions/126) discussion.

bindings/go/README.md

@@ -51,7 +51,7 @@ func main() {
 In order to build, you need to have the Go compiler installed. You can get it from [here](https://golang.org/dl/). Run the tests with:
 
 ```bash
-git clone https://github.com/ggerganov/whisper.cpp.git
+git clone https://github.com/ggml-org/whisper.cpp.git
 cd whisper.cpp/bindings/go
 make test
 ```
@@ -98,7 +98,7 @@ The API Documentation:
 
 Getting help:
 
-  * Follow the discussion for the go bindings [here](https://github.com/ggerganov/whisper.cpp/discussions/312)
+  * Follow the discussion for the go bindings [here](https://github.com/ggml-org/whisper.cpp/discussions/312)
 
 ## License
 

bindings/go/doc.go

@@ -1,5 +1,5 @@
 /*
-github.com/ggerganov/whisper.cpp/bindings/go
+github.com/ggml-org/whisper.cpp/bindings/go
 provides a speech-to-text service bindings for the Go programming language.
 */
 package whisper

bindings/java/README.md

@@ -31,10 +31,10 @@ public class Example {
             var whisperParams = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_GREEDY);
             // custom configuration if required
             whisperParams.temperature_inc = 0f;
-            
+
             var samples = readAudio(); // divide each value by 32767.0f
             whisper.fullTranscribe(whisperParams, samples);
-            
+
             int segmentCount = whisper.getTextSegmentCount(context);
             for (int i = 0; i < segmentCount; i++) {
                 String text = whisper.getTextSegment(context, i);
@@ -52,7 +52,7 @@ public class Example {
 In order to build, you need to have the JDK 8 or higher installed. Run the tests with:
 
 ```bash
-git clone https://github.com/ggerganov/whisper.cpp.git
+git clone https://github.com/ggml-org/whisper.cpp.git
 cd whisper.cpp/bindings/java
 
 ./gradlew build

bindings/ruby/README.md

@@ -228,7 +228,7 @@ The second argument `samples` may be an array, an object with `length` and `each
 Development
 -----------
 
-    % git clone https://github.com/ggerganov/whisper.cpp.git
+    % git clone https://github.com/ggml-org/whisper.cpp.git
     % cd whisper.cpp/bindings/ruby
     % rake test
 
@@ -241,5 +241,5 @@ License
 
 The same to [whisper.cpp][].
 
-[whisper.cpp]: https://github.com/ggerganov/whisper.cpp
-[models]: https://github.com/ggerganov/whisper.cpp/tree/master/models
+[whisper.cpp]: https://github.com/ggml-org/whisper.cpp
+[models]: https://github.com/ggml-org/whisper.cpp/tree/master/models

examples/bench/README.md

@@ -4,7 +4,7 @@ A very basic tool for benchmarking the inference performance on your device. The
 the transformer on some random audio data and records the execution time. This way we can have an objective comparison
 of the performance of the model for various setups.
 
-Benchmark results are tracked in the following Github issue: https://github.com/ggerganov/whisper.cpp/issues/89
+Benchmark results are tracked in the following Github issue: https://github.com/ggml-org/whisper.cpp/issues/89
 
 ```bash
 # run the bench too on the small.en model using 4 threads
@@ -40,7 +40,7 @@ system_info: n_threads = 4 | AVX2 = 0 | AVX512 = 0 | NEON = 1 | FP16_VA = 1 | WA
 
 If you wish, you can submit these results here:
 
-  https://github.com/ggerganov/whisper.cpp/issues/89
+  https://github.com/ggml-org/whisper.cpp/issues/89
 
 Please include the following information:
 

examples/command/command.cpp

@@ -3,7 +3,7 @@
 // Speak short text commands to the microphone.
 // This program will detect your voice command and convert them to text.
 //
-// ref: https://github.com/ggerganov/whisper.cpp/issues/171
+// ref: https://github.com/ggml-org/whisper.cpp/issues/171
 //
 
 #include "common-sdl.h"

examples/livestream.sh

@@ -2,7 +2,7 @@
 #
 # Transcribe audio livestream by feeding ffmpeg output to whisper.cpp at regular intervals
 # Idea by @semiformal-net
-# ref: https://github.com/ggerganov/whisper.cpp/issues/185
+# ref: https://github.com/ggml-org/whisper.cpp/issues/185
 #
 
 set -eo pipefail

examples/twitch.sh

@@ -2,7 +2,7 @@
 #
 # Transcribe twitch.tv livestream by feeding audio input to whisper.cpp at regular intervals
 # Thanks to @keyehzy
-# ref: https://github.com/ggerganov/whisper.cpp/issues/209
+# ref: https://github.com/ggml-org/whisper.cpp/issues/209
 #
 # The script currently depends on the third-party tool "streamlink"
 # On Mac OS, you can install it via "brew install streamlink"

examples/whisper.nvim/whisper.nvim

@@ -5,7 +5,7 @@
 # This simple script is called by Neovim to capture audio from the microphone and transcribe it with Whisper.
 # In order for this to work, you need to clone the whisper.cpp repo and build the 'stream' tool
 #
-#   git clone https://github.com/ggerganov/whisper.cpp
+#   git clone https://github.com/ggml-org/whisper.cpp
 #   cd whisper.cpp
 #   make stream
 #
@@ -31,7 +31,7 @@
 model="base.en"
 
 # export the path to the whisper.cpp repo in the WHISPER_CPP_HOME env variable
-# https://github.com/ggerganov/whisper.cpp
+# https://github.com/ggml-org/whisper.cpp
 cd "${WHISPER_CPP_HOME}"
 
 if [ ! -f ./stream ] ; then

examples/whisper.wasm/README.md

@@ -30,7 +30,7 @@ Link: https://ggerganov.github.io/whisper.cpp/
 
 ```bash (v3.1.2)
 # build using Emscripten
-git clone https://github.com/ggerganov/whisper.cpp
+git clone https://github.com/ggml-org/whisper.cpp
 cd whisper.cpp
 mkdir build-em && cd build-em
 emcmake cmake ..

examples/yt-wsp.sh

@@ -25,12 +25,12 @@
 # SOFTWARE.
 
 # Small shell script to more easily automatically download and transcribe live stream VODs.
-# This uses YT-DLP, ffmpeg and the CPP version of Whisper: https://github.com/ggerganov/whisper.cpp
+# This uses YT-DLP, ffmpeg and the CPP version of Whisper: https://github.com/ggml-org/whisper.cpp
 # Use `./examples/yt-wsp.sh help` to print help info.
 #
 # Sample usage:
 #
-#   git clone https://github.com/ggerganov/whisper.cpp
+#   git clone https://github.com/ggml-org/whisper.cpp
 #   cd whisper.cpp
 #   make
 #   ./examples/yt-wsp.sh https://www.youtube.com/watch?v=1234567890
@@ -44,7 +44,7 @@ SCRIPT_DIR="${SCRIPT_PATH%/*}"
 
 ################################################################################
 # Documentation on downloading models can be found in the whisper.cpp repo:
-# https://github.com/ggerganov/whisper.cpp/#usage
+# https://github.com/ggml-org/whisper.cpp/#usage
 #
 # note: unless a multilingual model is specified, WHISPER_LANG will be ignored
 # and the video will be transcribed as if the audio were in the English language
@@ -103,10 +103,10 @@ check_requirements() {
     fi;
 
     if ! command -v "${WHISPER_EXECUTABLE}" &>/dev/null; then
-        echo "The C++ implementation of Whisper is required: https://github.com/ggerganov/whisper.cpp"
+        echo "The C++ implementation of Whisper is required: https://github.com/ggml-org/whisper.cpp"
         echo "Sample usage:";
         echo "";
-        echo "  git clone https://github.com/ggerganov/whisper.cpp";
+        echo "  git clone https://github.com/ggml-org/whisper.cpp";
         echo "  cd whisper.cpp";
         echo "  make";
         echo "  ./examples/yt-wsp.sh https://www.youtube.com/watch?v=1234567890";

models/README.md

@@ -24,8 +24,7 @@ You can now use it like this:
 
 `ggml` models are available from the following locations:
 
-- https://huggingface.co/ggerganov/whisper.cpp/tree/main
-- https://ggml.ggerganov.com
+- https://huggingface.co/ggml-org/whisper.cpp/tree/main
 
 ### 3. Convert with [convert-pt-to-ggml.py](convert-pt-to-ggml.py)
 
@@ -78,7 +77,7 @@ OpenAI format. To read the HF models you can use the [convert-h5-to-ggml.py](con
 
 ```bash
 git clone https://github.com/openai/whisper
-git clone https://github.com/ggerganov/whisper.cpp
+git clone https://github.com/ggml-org/whisper.cpp
 
 # clone HF fine-tuned model (this is just an example)
 git clone https://huggingface.co/openai/whisper-medium
@@ -96,7 +95,7 @@ Currently, the chunk-based transcription strategy is not implemented, so there c
 ```bash
 # clone OpenAI whisper and whisper.cpp
 git clone https://github.com/openai/whisper
-git clone https://github.com/ggerganov/whisper.cpp
+git clone https://github.com/ggml-org/whisper.cpp
 
 # get the models
 cd whisper.cpp/models

models/convert-h5-to-ggml.py

@@ -3,7 +3,7 @@
 # Usage:
 #
 #   git clone https://github.com/openai/whisper
-#   git clone https://github.com/ggerganov/whisper.cpp
+#   git clone https://github.com/ggml-org/whisper.cpp
 #   git clone https://huggingface.co/openai/whisper-medium
 #
 #   python3 ./whisper.cpp/models/convert-h5-to-ggml.py ./whisper-medium/ ./whisper .
@@ -12,7 +12,7 @@
 #
 # For more info:
 #
-#   https://github.com/ggerganov/whisper.cpp/issues/157
+#   https://github.com/ggml-org/whisper.cpp/issues/157
 #
 
 import io

src/whisper.cpp

@@ -5529,7 +5529,7 @@ int whisper_full_with_state(
 
     // if length of spectrogram is less than 1.0s (100 frames), then return
     // basically don't process anything that is less than 1.0s
-    // see issue #39: https://github.com/ggerganov/whisper.cpp/issues/39
+    // see issue #39: https://github.com/ggml-org/whisper.cpp/issues/39
     if (seek_end < seek_start + 100) {
         WHISPER_LOG_WARN("%s: input is too short - %d ms < 1000 ms. consider padding the input audio with silence\n", __func__, (seek_end - seek_start)*10);
         return 0;
@@ -6375,7 +6375,7 @@ int whisper_full_with_state(
                 }
             }
 
-            // ref: https://github.com/ggerganov/whisper.cpp/pull/2629
+            // ref: https://github.com/ggml-org/whisper.cpp/pull/2629
             const bool single_timestamp_ending = tokens_cur.size() > 1 &&
                 tokens_cur[tokens_cur.size() - 2].id < whisper_token_beg(ctx) &&
                 tokens_cur[tokens_cur.size() - 1].id > whisper_token_beg(ctx);