Automatic Speech Recognition
Transformers
PyTorch
JAX
Tamil
whisper
whisper-event
Eval Results (legacy)
Instructions to use vasista22/whisper-tamil-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vasista22/whisper-tamil-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vasista22/whisper-tamil-small")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("vasista22/whisper-tamil-small") model = AutoModelForSpeechSeq2Seq.from_pretrained("vasista22/whisper-tamil-small") - Notebooks
- Google Colab
- Kaggle
Converting to ggml for whisper.cpp use
#3
by Reggie - opened
Hello,
I'm trying to convert the model into ggml format to use in whisper.cpp. Unfortunately when I run the command as recommended over at whisper.cpp:
!python3 ggml-to-pt.py pytorch_model.bin whisper.cpp/ ggml-tamil-small-vasista.bin
I get the following error:
Magic number: 67324752
Vocab size: 134742016
Audio context size: 0
Audio state size: 0
Audio head size: 0
Audio layer size: 0
Text context size: 1048576
Text head size: 1986619491
Mel size: 1882087796
Filters shape 0: 1515847694
Filters shape 1: 1515870810
Traceback (most recent call last):
File "/content/ggml-to-pt.py", line 48, in <module>
mel_filters = np.zeros((filters_shape_0, filters_shape_1))
ValueError: array is too big; `arr.size * arr.dtype.itemsize` is larger than the maximum possible size.
Any recommendations on how to fix this? I'm having the same issue with the medium model as well.
Reggie changed discussion status to closed
Sorted this out. Please ignore.