```markdown # Whisper Large v2 Uzbek Speech Recognition Model This project contains a fine-tuned version of the Faster Whisper Large v2 model for Uzbek speech recognition. The model can be used to transcribe Uzbek audio files into text. ## Installation 1. Ensure you have Python 3.7 or higher installed. 2. Install the required libraries: pip install transformers datasets accelerate soundfile librosa torch ## Usage You can use the model with the following Python code: ```python from transformers import pipeline, WhisperForConditionalGeneration, WhisperProcessor import torch # Load the model and processor model_name = "totetecdev/whisper-large-v2-uzbek-100steps" model = WhisperForConditionalGeneration.from_pretrained(model_name) processor = WhisperProcessor.from_pretrained(model_name) # Create the speech recognition pipeline pipe = pipeline( "automatic-speech-recognition", model=model, tokenizer=processor.tokenizer, feature_extractor=processor.feature_extractor, torch_dtype=torch.float16, device_map="auto", ) # Transcribe an audio file audio_file = "path/to/your/audio/file.wav" # Replace with the path to your audio file result = pipe(audio_file) print(result["text"]) ``` ## Example Usage 1. Prepare your audio file (it should be in WAV format). 2. Save the above code in a Python file (e.g., `transcribe.py`). 3. Update the `model_name` and `audio_file` variables in the code with your values. 4. Run the following command in your terminal or command prompt: ``` python transcribe.py ``` 5. The transcribed text will be displayed on the screen. ## Notes - This model will perform best with Uzbek audio files. - Longer audio files may require more processing time. - GPU usage is recommended, but the model can also run on CPU. - If you're using Google Colab, you can upload your audio file using: ```python from google.colab import files uploaded = files.upload() audio_file = next(iter(uploaded)) ``` ## Model Details - Base Model: Faster Whisper Large v2 - Fine-tuned for: Uzbek Speech Recognition ## License This project is licensed under [LICENSE]. See the LICENSE file for details. ## Contact For questions or feedback, please contact [KHABIB SALIMOV] at [totetec.dev@gmail.com]. ## Acknowledgements - OpenAI for the original Whisper model ```