metadata
license: cc-by-nc-4.0
language: ca
tags:
- audio
- automatic-speech-recognition
- whisper-large-v3
- projecte-aina
- barcelona-supercomputing-center
model-index:
- name: CLiC-UB/faster-whisper-large-v3-ca-rapnic-paralysis-full
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Rapnic (Test)
type: CLiC-UB/rapnic-example
split: test
args:
language: ca
metrics:
- name: WER
type: wer
value: 27.49
base_model:
- BSC-LT/whisper-large-v3-ca-punctuated-3370h
pipeline_tag: automatic-speech-recognition
library_name: transformers
faster-whisper-large-v3-ca-rapnic-paralysis-full
Table of Contents
Click to expand
Model Description
Faster Whisper conversion of CLiC-UB/whisper-large-v3-ca-rapnic-paralysis-full
How to Get Started with the Model
Installation
To use this model, you may install faster-whisper
Create a virtual environment:
python -m venv /path/to/venv
Activate the environment:
source /path/to/venv/bin/activate
Install the modules:
pip install faster-whisper
For Inference
To transcribe audio in Catalan using this model, you can follow this example:
from faster_whisper import WhisperModel
model_size = "CLiC-UB/faster-whisper-large-v3-ca-rapnic-paralysis-full"
# Run on GPU with FP16
model = WhisperModel(model_size, device="cuda", compute_type="float16")
# or run on GPU with INT8
#model = WhisperModel(model_size, device="cuda", compute_type="int8_float16")
# or run on CPU with INT8
# model = WhisperModel(model_size, device="cpu", compute_type="int8")
segments, info = model.transcribe("audio_in_catalan.mp3", beam_size=5, task="transcribe",language="ca")
print("Detected language '%s' with probability %f" % (info.language, info.language_probability))
for segment in segments:
print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
Conversion Details
Conversion procedure
This model is not a direct result of training. It is a conversion of a Whisper model using faster-whisper. The procedure to create the model is as follows:
ct2-transformers-converter --model CLiC-UB/whisper-large-v3-ca-rapnic-paralysis-full
--output_dir faster-whisper-large-v3-ca-rapnic-paralysis-full
--copy_files preprocessor_config.json tokenizer.json
Additional Information
Contact
For further information, please send an email to gr.clic@ub.edu.