Create README.md

README.md

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+---
+pipeline_tag: automatic-speech-recognition
+datasets:
+- mozilla-foundation/common_voice_11_0
+---
+# Model description
+
+This model is an openai's whisper-small model fine-tuned on the Kinyarwanda common-voice dataset. The Kinyarwanda language was added by fine-tuning on top of the Swahili language.
+It achieves a 24 WER. Currently, it does not provide Kinyarwanda-to-English translation.
+
+# Usage
+```python
+>>> from transformers import WhisperProcessor, WhisperForConditionalGeneration
+>>> from datasets import load_dataset
+>>> import datasets
+>>> import torch
+>>> # load model and processor
+>>> processor = WhisperProcessor.from_pretrained("mbazaNLP/Whisper-Small-Kinyarwanda")
+>>> model = WhisperForConditionalGeneration.from_pretrained("mbazaNLP/Whisper-Small-Kinyarwanda")
+>>> ds = load_dataset("common_voice", "rw", split="test", streaming=True)
+>>> ds = ds.cast_column("audio", datasets.Audio(sampling_rate=16_000))
+>>> input_speech = next(iter(ds))["audio"]["array"]
+>>> model.config.forced_decoder_ids = processor.get_decoder_prompt_ids(language = "sw", task = "transcribe")
+>>> input_features = processor(input_speech, return_tensors="pt").input_features 
+>>> predicted_ids = model.generate(input_features)
+>>> transcription = processor.batch_decode(predicted_ids)
+['<|startoftranscript|><|sw|><|transcribe|><|notimestamps|>Abamugariye ku rugamba bafashwa kubona insimburangingo<|endoftext|>']
+>>> transcription = processor.batch_decode(predicted_ids, skip_special_tokens = True)
+['Abamugariye ku rugamba bafashwa kubona insimburangingo']
+
+```