Update README.md

README.md

@@ -258,6 +258,41 @@ result = pipe(sample)
 print(result["text"])
 ```
 
+### Transcription with Prompt
+Kotoba-whisper can generate transcription with prompting as below:
+
+```python
+import torch
+from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
+from datasets import load_dataset, Audio
+
+# config
+model_id = "kotoba-tech/kotoba-whisper-v1.0"
+torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+# load model
+model = AutoModelForSpeechSeq2Seq.from_pretrained(model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True)
+model.to(device)
+processor = AutoProcessor.from_pretrained(model_id)
+
+# load sample audio & downsample to 16kHz
+dataset = load_dataset("japanese-asr/ja_asr.reazonspeech_test", split="test")
+dataset = dataset.cast_column("audio", Audio(sampling_rate=16000))
+input_features = processor(dataset[10]["audio"]["array"], return_tensors="pt").input_features
+
+# --- Without prompt ---
+output_without_prompt = model.generate(input_features)
+print(processor.decode(output_without_prompt[0]))
+# <|startoftranscript|><|ko|><|transcribe|><|notimestamps|>81歳、力強い走りに変わってきます。<|endoftext|>
+
+# --- With prompt ---: Let's change `81` to `91`.
+prompt_ids = processor.get_prompt_ids("91歳", return_tensors="pt")
+output_with_prompt = model.generate(input_features, prompt_ids=prompt_ids)
+print(processor.decode(output_with_prompt[0]))
+# <|startofprev|> 91歳<|startoftranscript|><|ko|><|transcribe|><|notimestamps|> あっぶったでもスルガさん、91歳、力強い走りに変わってきます。<|endoftext|>
+```
+
 ### Additional Speed & Memory Improvements
 You can apply additional speed and memory improvements to further reduce the inference speed and VRAM 
 requirements. These optimisations primarily target the attention kernel, swapping it from an eager implementation to a