Description
In case of Q8/Q5 models the output is garbage:
.\whisper-cli.exe -m ....\models\ggml-large-v3-turbo-q8_0.bin -f "out.mp3" -l en -of meeting -otxt
whisper_init_from_file_with_params_no_state: loading model from '....\models\ggml-large-v3-turbo-q8_0.bin'
whisper_init_with_params_no_state: use gpu = 1
whisper_init_with_params_no_state: flash attn = 0
whisper_init_with_params_no_state: gpu_device = 0
whisper_init_with_params_no_state: dtw = 0
ggml_vulkan: Found 1 Vulkan devices:
ggml_vulkan: 0 = Intel(R) Graphics (Intel Corporation) | uma: 1 | fp16: 1 | warp size: 32 | shared memory: 32768 | int dot: 1 | matrix cores: none
whisper_init_with_params_no_state: devices = 2
whisper_init_with_params_no_state: backends = 2
whisper_model_load: loading model
whisper_model_load: n_vocab = 51866
whisper_model_load: n_audio_ctx = 1500
whisper_model_load: n_audio_state = 1280
whisper_model_load: n_audio_head = 20
whisper_model_load: n_audio_layer = 32
whisper_model_load: n_text_ctx = 448
whisper_model_load: n_text_state = 1280
whisper_model_load: n_text_head = 20
whisper_model_load: n_text_layer = 4
whisper_model_load: n_mels = 128
whisper_model_load: ftype = 7
whisper_model_load: qntvr = 2
whisper_model_load: type = 5 (large v3)
whisper_model_load: adding 1609 extra tokens
whisper_model_load: n_langs = 100
whisper_model_load: Vulkan0 total size = 873.55 MB
whisper_model_load: model size = 873.55 MB
whisper_backend_init_gpu: using Vulkan0 backend
whisper_init_state: kv self size = 10.49 MB
whisper_init_state: kv cross size = 31.46 MB
whisper_init_state: kv pad size = 7.86 MB
whisper_init_state: compute buffer (conv) = 37.67 MB
whisper_init_state: compute buffer (encode) = 212.29 MB
whisper_init_state: compute buffer (cross) = 9.25 MB
whisper_init_state: compute buffer (decode) = 100.03 MB
system_info: n_threads = 4 / 14 | WHISPER : COREML = 0 | OPENVINO = 0 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX_VNNI = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | OPENMP = 1 | AARCH64_REPACK = 1 |
main: processing 'out.mp3' (67817473 samples, 4238.6 sec), 4 threads, 1 processors, 5 beams + best of 5, lang = en, task = transcribe, timestamps = 1 ...
[00:00:00.000 --> 00:00:03.160] and
[00:00:03.160 --> 00:00:05.660] ,
[00:00:05.660 --> 00:00:11.780] ,
[00:00:11.780 --> 00:00:27.180] ,
The same with FP16 model:
.\whisper-cli.exe -m ....\models\ggml-large-v3-turbo.bin -f "out.mp3" -l en -of meeting -otxt -t 6
whisper_init_from_file_with_params_no_state: loading model from '....\models\ggml-large-v3-turbo.bin'
whisper_init_with_params_no_state: use gpu = 1
whisper_init_with_params_no_state: flash attn = 0
whisper_init_with_params_no_state: gpu_device = 0
whisper_init_with_params_no_state: dtw = 0
ggml_vulkan: Found 1 Vulkan devices:
ggml_vulkan: 0 = Intel(R) Graphics (Intel Corporation) | uma: 1 | fp16: 1 | warp size: 32 | shared memory: 32768 | int dot: 1 | matrix cores: none
whisper_init_with_params_no_state: devices = 2
whisper_init_with_params_no_state: backends = 2
whisper_model_load: loading model
whisper_model_load: n_vocab = 51866
whisper_model_load: n_audio_ctx = 1500
whisper_model_load: n_audio_state = 1280
whisper_model_load: n_audio_head = 20
whisper_model_load: n_audio_layer = 32
whisper_model_load: n_text_ctx = 448
whisper_model_load: n_text_state = 1280
whisper_model_load: n_text_head = 20
whisper_model_load: n_text_layer = 4
whisper_model_load: n_mels = 128
whisper_model_load: ftype = 1
whisper_model_load: qntvr = 0
whisper_model_load: type = 5 (large v3)
whisper_model_load: adding 1609 extra tokens
whisper_model_load: n_langs = 100
whisper_model_load: Vulkan0 total size = 1623.92 MB
whisper_model_load: model size = 1623.92 MB
whisper_backend_init_gpu: using Vulkan0 backend
whisper_init_state: kv self size = 10.49 MB
whisper_init_state: kv cross size = 31.46 MB
whisper_init_state: kv pad size = 7.86 MB
whisper_init_state: compute buffer (conv) = 37.67 MB
whisper_init_state: compute buffer (encode) = 212.29 MB
whisper_init_state: compute buffer (cross) = 9.25 MB
whisper_init_state: compute buffer (decode) = 100.03 MB
system_info: n_threads = 6 / 14 | WHISPER : COREML = 0 | OPENVINO = 0 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX_VNNI = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | OPENMP = 1 | AARCH64_REPACK = 1 |
main: processing 'out.mp3' (67817473 samples, 4238.6 sec), 6 threads, 1 processors, 5 beams + best of 5, lang = en, task = transcribe, timestamps = 1 ...
[00:00:00.000 --> 00:00:07.680] Talking about ecosystem from infrastructure architecture...