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README.md

@@ -101,7 +101,7 @@ LibriSpeech is used here as an independent check on the extent of degradation ca
 
 ## Inference
 ### Quick Demo (3 samples)
-Copy/paste to transcribe the first three rows from a HuggingFace dataset with `transcribe-en_us-spelling-v1-tiny`:
+Copy/paste to transcribe the first three rows from a HuggingFace dataset with `Trelis/transcribe-en_us-spelling-v1-tiny`:
 
 ```bash
 uv run --with datasets --with transformers --with torchaudio python - <<'PY'
@@ -109,7 +109,7 @@ from datasets import load_dataset
 from transformers import pipeline
 
 DATASET_ID = "Trelis/transcribe-to-en_GB-v1"
-MODEL_ID = "transcribe-en_us-spelling-v1-tiny"
+MODEL_ID = "Trelis/transcribe-en_us-spelling-v1-tiny"
 
 print(f"Loading dataset: {DATASET_ID} (first 3 rows)")
 dataset = load_dataset(DATASET_ID, split="test[:3]")
@@ -136,7 +136,7 @@ uv run --with transformers --with torchaudio python - <<'PY'
 from transformers import pipeline
 import torchaudio
 
-MODEL_ID = "transcribe-en_us-spelling-v1-tiny"
+MODEL_ID = "Trelis/transcribe-en_us-spelling-v1-tiny"
 audio_path = "/path/to/audio.wav"  # change me
 
 audio, sr = torchaudio.load(audio_path)