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typhoon-ai
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Model Details
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typhoon-ai
Model Tree
Input Modalities
Output Modalities
Supported Functionality
python
from transformers import WhisperProcessor, WhisperForConditionalGenerationimport torchaudioimport torchmodel_path = "scb10x/monsoon-whisper-medium-gigaspeech2"device = "cuda"filepath = 'audio.wav'processor = WhisperProcessor.from_pretrained(model_path)model = WhisperForConditionalGeneration.from_pretrained(model_path, torch_dtype=torch.bfloat16)model.to(device)model.eval()model.config.forced_decoder_ids = processor.get_decoder_prompt_ids(language="th", task="transcribe")array, sr = torchaudio.load(filepath)input_features = (processor(array, sampling_rate=sr, return_tensors="pt").to(device).to(torch.bfloat16).input_features)predicted_ids = model.generate(input_features)transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)print(transcription)
| Model | WER (GS2) | WER (CV17) | CER (GS2) | CER (CV17) |
|---|---|---|---|---|
| whisper-large-v3 | 37.02 | 22.63 | 24.03 | 8.49 |
| whisper-medium | 55.64 | 43.01 | 37.55 | 16.41 |
| biodatlab-whisper-th-medium-combined | 31.00 | 14.25 | 21.20 | 5.69 |
| biodatlab-whisper-th-large-v3-combined | 29.02 | 15.72 | 19.96 | 6.32 |
| monsoon-whisper-medium-gigaspeech2 | 22.74 |
This model is experimental and may not always be accurate. Developers should carefully assess potential risks in the context of their specific applications.
Kunat Pipatanakul, Potsawee Manakul, Sittipong Sripaisarnmongkol, Natapong Nitarach, Warit Sirichotedumrong, Adisai Na-Thalang, Phatrasek Jirabovonvisut, Parinthapat Pengpun, Krisanapong Jirayoot, Pathomporn Chokchainant, Kasima Tharnpipitchai
| 20.79 |
| 14.15 |
| 6.92 |