| # Whisper Tiny Fine-tuned on Kalaallisut | |
| This model is a fine-tuned version of the [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on a very small dataset of the Kalaallisut (Greenlandic) language. Whisper is a general-purpose speech recognition model trained on a large-scale dataset. However, this fine-tuned version on Kalaallisut is **not fully reliable** due to the limited amount of training data. | |
| ### Model Details | |
| - **Model**: Whisper Tiny Fine-tuned on Kalaallisut | |
| - **Base Model**: [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) | |
| - **Training Data**: A very small amount of audio-transcription pairs in Kalaallisut | |
| - **Purpose**: Speech-to-text for the Kalaallisut language | |
| - **License**: [MIT License](https://opensource.org/licenses/MIT) | |
| ### Training Data | |
| This model was fine-tuned on a small dataset of the Kalaallisut language. The dataset was **not comprehensive** and **does not cover all aspects** of the language. As a result, the model is not reliable for general use cases and may produce incorrect transcriptions. | |
| ### Limitations | |
| - The model has been trained on a **very small dataset** (only a few hours of audio). | |
| - The **transcriptions may not be accurate**, especially for more complex audio inputs. | |
| - This model is a **proof of concept** and not intended for production use. | |
| ### Intended Use | |
| The model can be used for: | |
| - Experimentation and testing with Kalaallisut language speech-to-text tasks. | |
| - It may be helpful for small projects or as a foundation for further fine-tuning with more data. | |
| ### Usage Example | |
| You can use the model for transcription with the following code: | |
| ```python | |
| from transformers import WhisperProcessor, WhisperForConditionalGeneration | |
| import torch | |
| # Load the model and processor | |
| processor = WhisperProcessor.from_pretrained("VoiceLessQ/whisper-tiny-kalaallisut") | |
| model = WhisperForConditionalGeneration.from_pretrained("VoiceLessQ/whisper-tiny-kalaallisut") | |
| # Load and process an audio file | |
| audio_array = ... # Load your audio file here | |
| input_features = processor(audio_array, sampling_rate=16000, return_tensors="pt").input_features | |
| # Generate transcription | |
| generated_ids = model.generate(input_features) | |
| transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)[0] | |
| print(f"Transcription: {transcription}") | |