Georgi Gerganov b0502836b8
whisper : add full CUDA and Metal offloading (#1472)
* whisper : migrate to ggml-backend

* whisper : fix logit reading

* whisper : fix tensor allocation during load

* whisper : fix beam-search with CUDA

* whisper : free backends + fix compile warning

* whisper : print when CUDA is enabled

* whisper : fix CoreML

* make : clean-up

* talk : fix compile warning

* whisper : support ggml_conv with CUDA and Metal (#1473)

* ggml : add CUDA support for ggml_conv

* whisper : remove ggml_repeat for conv bias + single backend

* cuda : fix im2col kernel

* metal : add im2col support + mul mat-vec f16 x f16

* bench-all : add q4 models

* whisper : clean-up

* quantize-all : fix

* ggml : im2col opts

* whisper : avoid whisper_model_data wrapper

* whisper : add note that ggml_mul_mat_pad does not work with CUDA

* whisper : factor out graph compute in common function

* whisper : fixes

* whisper : fix UB with measure buffers

* whisper : try to fix the parallel whisper_state functionality (#1479)

* whisper : try to fix the parallel whisper_state functionality

* whisper : fix multi-state Metal

* whisper : free backend instances in whisper_state
2023-11-12 15:31:08 +02:00
..
2023-06-01 22:45:00 +10:00
2023-06-01 22:45:00 +10:00
2023-06-01 22:45:00 +10:00

talk

Talk with an Artificial Intelligence in your terminal

Demo Talk

Web version: examples/talk.wasm

Building

The talk tool depends on SDL2 library to capture audio from the microphone. You can build it like this:

# Install SDL2 on Linux
sudo apt-get install libsdl2-dev

# Install SDL2 on Mac OS
brew install sdl2

# Build the "talk" executable
make talk

# Run it
./talk -p Santa

GPT-2

To run this, you will need a ggml GPT-2 model: instructions

Alternatively, you can simply download the smallest ggml GPT-2 117M model (240 MB) like this:

wget --quiet --show-progress -O models/ggml-gpt-2-117M.bin https://huggingface.co/ggerganov/ggml/resolve/main/ggml-model-gpt-2-117M.bin

TTS

For best experience, this example needs a TTS tool to convert the generated text responses to voice. You can use any TTS engine that you would like - simply edit the speak script to your needs. By default, it is configured to use MacOS's say or espeak or Windows SpeechSynthesizer, but you can use whatever you wish.