Open athoune opened 10 months ago
Thank you, that helped!
>>> import whispercpp
>>> whispercpp.MODELS["ggml-large-v3.bin"] = "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3.bin"
>>> w_large = whispercpp.Whisper('large-v3')
Downloading ggml-large-v3.bin...
whisper_init_from_file_no_state: loading model from '/Users/micseydel/.ggml-models/ggml-large-v3.bin'
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 = 32
whisper_model_load: n_mels = 128
whisper_model_load: f16 = 1
whisper_model_load: type = 5
whisper_model_load: mem required = 3342.00 MB (+ 71.00 MB per decoder)
whisper_model_load: adding 1609 extra tokens
whisper_model_load: model ctx = 2951.32 MB
whisper_model_load: model size = 2951.01 MB
whisper_init_state: kv self size = 70.00 MB
whisper_init_state: kv cross size = 234.38 MB
It seems like I must be doing something wrong though still
>>> result = w_large.transcribe("/Users/micseydel/transcriptions/2024-08-10/Tom Froese and Michael Levin discuss Tom's Irruption theory.mp4")
Loading data..
Transcribing..
whisper_full_with_state: progress = 5%
whisper_full_with_state: progress = 10%
whisper_full_with_state: progress = 15%
whisper_full_with_state: progress = 20%
whisper_full_with_state: progress = 25%
whisper_full_with_state: progress = 30%
whisper_full_with_state: progress = 35%
whisper_full_with_state: progress = 40%
whisper_full_with_state: progress = 45%
whisper_full_with_state: progress = 50%
whisper_full_with_state: progress = 55%
whisper_full_with_state: progress = 60%
whisper_full_with_state: progress = 65%
whisper_full_with_state: progress = 70%
whisper_full_with_state: progress = 75%
whisper_full_with_state: progress = 80%
whisper_full_with_state: progress = 85%
whisper_full_with_state: progress = 90%
whisper_full_with_state: progress = 95%
whisper_full_with_state: progress = 100%
>>> text = w_large.extract_text(result)
Extracting text...
>>> len(text)
0
>>> type(result)
<class 'int'>
>>> result
0
>>> text
[]
large
model doesn't work :You have to pick v1, v2 or v3.
See https://huggingface.co/ggerganov/whisper.cpp/tree/main