Create README.md

README.md

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+---
+language: ko
+tags:
+  - text-to-speech
+license: other
+---
+
+# Torchaudio_Tacotron2_kss
+
+torchaudio [Tacotron2](https://pytorch.org/audio/stable/generated/torchaudio.models.Tacotron2.html#torchaudio.models.Tacotron2) model, trained on kss dataset.
+
+## License
+
+- code: MIT License
+- `pytorch_model.bin` weights: CC BY-NC-SA 4.0 (license of the kss dataset)
+
+## Requirements
+
+```sh
+pip install torch torchaudio transformers phonemizer
+```
+
+and you have to install [`espeak-ng`](https://github.com/espeak-ng/espeak-ng)
+
+If you are using Windows, you need to set additional environment variables. see: <https://github.com/bootphon/phonemizer/issues/44>
+
+## Usage
+
+```python
+import torch
+from transformers import AutoModel, AutoTokenizer
+
+repo = "Bingsu/torchaudio_tacotron2_kss"
+model = AutoModel.from_pretrained(
+    repo,
+    trust_remote_code=True,
+    revision="589d6557e8b4bb347f49de74270541063ba9c2bc"
+    )
+tokenizer = AutoTokenizer.from_pretrained(repo)
+model.eval()
+```
+
+```python
+vocoder = torch.hub.load("seungwonpark/melgan:aca59909f6dd028ec808f987b154535a7ca3400c", "melgan", trust_repo=True, pretrained=False)
+url = "https://huggingface.co/Bingsu/torchaudio_tacotron2_kss/resolve/main/melgan.pt"
+state_dict = torch.hub.load_state_dict_from_url(url)
+vocoder.load_state_dict(state_dict)
+```
+
+vocoder is same as original [seungwonpark/melgan](https://github.com/seungwonpark/melgan), but the weights are on the cuda, so I brought them separately.
+
+```python
+text = "반갑습니다 타코트론2입니다."
+inp = tokenizer(text, return_tensors="pt", return_length=True, return_attention_mask=False)
+```
+
+```python
+with torch.inference_mode():
+    out = model(**inp)
+    audio = vocoder(out[0])
+```
+
+```python
+import IPython.display as ipd
+
+ipd.Audio(audio[0].numpy(), rate=22050)
+```
+
+<audio src="https://huggingface.co/Bingsu/torchaudio_tacotron2_kss/resolve/main/examples/sample1.wav" controls>