forked from extern/whisper.cpp
talk.wasm : move to https://whisper.ggerganov.com/talk
This way, we can share the same models across different WASM examples and not have to download them for each page
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@ -4,7 +4,7 @@ Talk with an Artificial Intelligence in your browser:
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https://user-images.githubusercontent.com/1991296/203411580-fedb4839-05e4-4474-8364-aaf1e9a9b615.mp4
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Online demo: https://talk.ggerganov.com
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Online demo: https://whisper.ggerganov.com/talk/
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## How it works?
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@ -50,6 +50,22 @@ on a phone or a tablet. Hopefully, in the near future this will become supported
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- Better UI (contributions are welcome)
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- Better GPT-2 prompting
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## Build instructions
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```bash
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# build using Emscripten (v3.1.2)
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git clone https://github.com/ggerganov/whisper.cpp
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cd whisper.cpp
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mkdir build-em && cd build-em
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emcmake cmake ..
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make -j
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# copy the produced page to your HTTP path
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cp bin/talk.wasm/index.html /path/to/html/
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cp bin/talk.wasm/talk.js /path/to/html/
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cp bin/libtalk.worker.js /path/to/html/
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```
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## Feedback
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If you have any comments or ideas for improvement, please drop a comment in the following discussion:
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@ -35,7 +35,7 @@
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<ul>
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<li><a href="https://github.com/ggerganov/whisper.cpp">OpenAI's Whisper</a> to listen to you as you speak in the microphone</li>
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<li><a href="https://github.com/ggerganov/ggml/tree/master/examples/gpt-2">OpenAI's GPT-2</a> to generate text responses</li>
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<li><a href="https://github.com/ggerganov/whisper.cpp/tree/master/examples/talk.wasm">OpenAI's GPT-2</a> to generate text responses</li>
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<li><a href="https://developer.mozilla.org/en-US/docs/Web/API/Web_Speech_API">Web Speech API</a> to vocalize the responses through your speakers</li>
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</ul>
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@ -283,7 +283,7 @@
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}
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let dbVersion = 1
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let dbName = 'talk.ggerganov.com';
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let dbName = 'whisper.ggerganov.com';
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let indexedDB = window.indexedDB || window.mozIndexedDB || window.webkitIndexedDB || window.msIndexedDB
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// fetch a remote file from remote URL using the Fetch API
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@ -439,8 +439,8 @@
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function loadWhisper(model) {
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let urls = {
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'tiny.en': 'https://talk.ggerganov.com/ggml-model-whisper-tiny.en.bin',
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'base.en': 'https://talk.ggerganov.com/ggml-model-whisper-base.en.bin',
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'tiny.en': 'https://whisper.ggerganov.com/ggml-model-whisper-tiny.en.bin',
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'base.en': 'https://whisper.ggerganov.com/ggml-model-whisper-base.en.bin',
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};
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let sizes = {
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@ -464,8 +464,8 @@
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function loadGPT2(model) {
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let urls = {
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'small': 'https://talk.ggerganov.com/ggml-model-gpt-2-117M.bin',
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'medium': 'https://talk.ggerganov.com/ggml-model-gpt-2-345M.bin',
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'small': 'https://whisper.ggerganov.com/ggml-model-gpt-2-117M.bin',
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'medium': 'https://whisper.ggerganov.com/ggml-model-gpt-2-345M.bin',
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};
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let sizes = {
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@ -26,10 +26,9 @@ Link: https://whisper.ggerganov.com
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![image](https://user-images.githubusercontent.com/1991296/197348344-1a7fead8-3dae-4922-8b06-df223a206603.png)
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## Build instructions
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```bash
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```bash (v3.1.2)
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# build using Emscripten
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git clone https://github.com/ggerganov/whisper.cpp
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cd whisper.cpp
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@ -41,3 +40,4 @@ make -j
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cp bin/whisper.wasm/index.html /path/to/html/
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cp bin/whisper.wasm/whisper.js /path/to/html/
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cp bin/libwhisper.worker.js /path/to/html/
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```
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@ -52,7 +52,7 @@ There are community efforts for creating fine-tuned Whisper models using extra t
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Transformer implementation of Whisper. The produced models are in slightly different format compared to the original
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OpenAI format. To read the HF models you can use the [convert-h5-to-ggml.py](convert-h5-to-ggml.py) script like this:
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```
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```bash
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git clone https://github.com/openai/whisper
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git clone https://github.com/ggerganov/whisper.cpp
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