Update README.md

README.md

@@ -1,3 +1,55 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+---
+
+## Usage
+
+### Python
+
+```python
+import os
+import numpy as np
+from onnxruntime import InferenceSession
+
+# Tokens produced by phonemize() and tokenize() in kokoro.py
+tokens = [50, 157, 43, 135, 16, 53, 135, 46, 16, 43, 102, 16, 56, 156, 57, 135, 6, 16, 102, 62, 61, 16, 70, 56, 16, 138, 56, 156, 72, 56, 61, 85, 123, 83, 44, 83, 54, 16, 53, 65, 156, 86, 61, 62, 131, 83, 56, 4, 16, 54, 156, 43, 102, 53, 16, 156, 72, 61, 53, 102, 112, 16, 70, 56, 16, 138, 56, 44, 156, 76, 158, 123, 56, 16, 62, 131, 156, 43, 102, 54, 46, 16, 102, 48, 16, 81, 47, 102, 54, 16, 54, 156, 51, 158, 46, 16, 70, 16, 92, 156, 135, 46, 16, 54, 156, 43, 102, 48, 4, 16, 81, 47, 102, 16, 50, 156, 72, 64, 83, 56, 62, 16, 156, 51, 158, 64, 83, 56, 16, 44, 157, 102, 56, 16, 44, 156, 76, 158, 123, 56, 4]
+
+# Context length is 512, but leave room for the pad token 0 at the start & end
+assert len(tokens) <= 510, len(tokens)
+
+# Style vector based on len(tokens), ref_s has shape (1, 256)
+voices = np.fromfile('./voices/af.bin', dtype=np.float32).reshape(-1, 1, 256)
+ref_s = voices[len(tokens)]
+
+# Add the pad ids, and reshape tokens, should now have shape (1, <=512)
+tokens = [[0, *tokens, 0]]
+
+model_name = 'model.onnx' # Options: model.onnx, model_fp16.onnx, model_quantized.onnx, model_q8f16.onnx, model_uint8.onnx, model_uint8f16.onnx, model_q4.onnx, model_q4f16.onnx
+sess = InferenceSession(os.path.join('onnx', model_name))
+
+audio = sess.run(None, dict(
+    input_ids=tokens,
+    style=ref_s,
+    speed=np.ones(1, dtype=np.float32),
+))[0]
+```
+
+Optionally, save the audio to a file:
+```
+import scipy.io.wavfile as wavfile
+wavfile.write('audio.wav', 24000, audio[0])
+```
+
+## Samples
+
+| Model                                          | Size (MB) | Sample                                                                                                                                  |
+|------------------------------------------------|-----------|-----------------------------------------------------------------------------------------------------------------------------------------|
+| model.onnx (fp32)                              | 326       | <audio controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/njexBuqPzfYUvWgs9eQ-_.wav"></audio> |
+| model_fp16.onnx (fp16)                         | 163       | <audio controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/8Ebl44hMQonZs4MlykExt.wav"></audio> |
+| model_quantized.onnx (8-bit)                   | 92.4      | <audio controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/9SLOt6ETclZ4yRdlJ0VIj.wav"></audio> |
+| model_q8f16.onnx (Mixed precision)             | 86        | <audio controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/gNDMqb33YEmYMbAIv_Grx.wav"></audio> |
+| model_uint8.onnx (8-bit & mixed precision)     | 177       | <audio controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/tpOWRHIWwEb0PJX46dCWQ.wav"></audio> |
+| model_uint8f16.onnx (Mixed precision)          | 114       | <audio controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/vtZhABzjP0pvGD7dRb5Vr.wav"></audio> |
+| model_q4.onnx (4-bit matmul)                   | 305       | <audio controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/8FVn0IJIUfccEBWq8Fnw_.wav"></audio> |
+| model_q4f16.onnx (4-bit matmul & fp16 weights) | 154       | <audio controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/7DrgWC_1q00s-wUJuG44X.wav"></audio> |
+