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Add transformers usage

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Bark will be added to Transformers pretty soon! It is now time to update the model cars to mention the HF implementation!

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  1. README.md +57 -3
README.md CHANGED
@@ -38,7 +38,61 @@ Use at your own risk.
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  The following is additional information about the models released here.
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- ## Model Usage
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```python
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  from bark import SAMPLE_RATE, generate_audio, preload_models
@@ -52,10 +106,10 @@ text_prompt = """
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  Hello, my name is Suno. And, uh β€” and I like pizza. [laughs]
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  But I also have other interests such as playing tic tac toe.
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  """
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- audio_array = generate_audio(text_prompt)
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  # play text in notebook
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- Audio(audio_array, rate=SAMPLE_RATE)
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  ```
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  [pizza.webm](https://user-images.githubusercontent.com/5068315/230490503-417e688d-5115-4eee-9550-b46a2b465ee3.webm)
 
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  The following is additional information about the models released here.
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+ ## πŸ€— Transformers Usage
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+
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+
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+ You can run Bark locally with the πŸ€— Transformers library from version 4.31.0 onwards.
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+
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+ 1. First install the πŸ€— [Transformers library](https://github.com/huggingface/transformers) from main:
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+
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+ ```
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+ pip install git+https://github.com/huggingface/transformers.git
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+ ```
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+
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+ 2. Run the following Python code to generate speech samples:
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+
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+ ```python
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+ from transformers import AutoProcessor, AutoModel
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+
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+
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+ processor = AutoProcessor.from_pretrained("suno/bark-small")
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+ model = AutoModel.from_pretrained("suno/bark-small")
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+
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+ inputs = processor(
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+ text=["Hello, my name is Suno. And, uh β€” and I like pizza. [laughs] But I also have other interests such as playing tic tac toe."],
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+ return_tensors="pt",
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+ )
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+
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+ speech_values = model.generate_speech(**inputs, do_sample=True)
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+ ```
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+
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+ 3. Listen to the speech samples either in an ipynb notebook:
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+
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+ ```python
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+ from IPython.display import Audio
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+
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+ sampling_rate = model.config.sample_rate
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+ Audio(speech_values.cpu().numpy().squeeze(), rate=sampling_rate)
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+ ```
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+
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+ Or save them as a `.wav` file using a third-party library, e.g. `scipy`:
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+
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+ ```python
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+ import scipy
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+
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+ sampling_rate = model.config.sample_rate
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+ scipy.io.wavfile.write("bark_out.wav", rate=sampling_rate, data=speech_values.cpu().numpy().squeeze())
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+ ```
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+
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+ For more details on using the Bark model for inference using the πŸ€— Transformers library, refer to the [Bark docs](https://huggingface.co/docs/transformers/model_doc/bark).
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+ ## Suno Usage
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+ You can also run Bark locally through the original [Bark library]((https://github.com/suno-ai/bark):
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+ 1. First install the [`bark` library](https://github.com/suno-ai/bark)
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+ 3. Run the following Python code:
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  ```python
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  from bark import SAMPLE_RATE, generate_audio, preload_models
 
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  Hello, my name is Suno. And, uh β€” and I like pizza. [laughs]
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  But I also have other interests such as playing tic tac toe.
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  """
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+ speech_array = generate_audio(text_prompt)
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  # play text in notebook
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+ Audio(speech_array, rate=SAMPLE_RATE)
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  ```
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  [pizza.webm](https://user-images.githubusercontent.com/5068315/230490503-417e688d-5115-4eee-9550-b46a2b465ee3.webm)