suno/bark
suno/bark
2
1
Overview Code Discussions Pull Requests Wiki Activity

Update README.md (#32)

Browse Source 
- Update README.md (8f943aced9e2eb6f0d863cc6e8c600c1955ee509)
- Update README.md (e9a0292eee760619bef542411bf421816d153058)
- Update README.md (40e663a136de821ffb01bf0c71caafbc40096f88)
- Update README.md (e7fc53d8bd1776d3705573f8927f93c945c7f6e8)
- Update README.md (59ccf64c288c6c6dde3668c4531040c42563913c)


Co-authored-by: Vaibhav Srivastav <reach-vb@users.noreply.huggingface.co>
This commit is contained in:
Georg Kucsko 2023-10-04 14:17:55 +00:00 committed by system
parent a7b2a67129
commit 70a8a7d341
1 changed files with 21 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

30
README.md
View File

@ -69,23 +69,35 @@ Try out Bark yourself!
## 🤗 Transformers Usage
You can run Bark locally with the 🤗 Transformers library from version 4.31.0 onwards.
1. First install the 🤗 [Transformers library](https://github.com/huggingface/transformers) from main:
1. First install the 🤗 [Transformers library](https://github.com/huggingface/transformers) and scipy:
```
pip install git+https://github.com/huggingface/transformers.git
pip install --upgrade pip
pip install --upgrade transformers scipy
```
2. Run the following Python code to generate speech samples:
2. Run inference via the `Text-to-Speech` (TTS) pipeline. You can infer the bark model via the TTS pipeline in just a few lines of code!
```python
from transformers import pipeline
import scipy
synthesiser = pipeline("text-to-speech", "suno/bark")
speech = synthesiser("Hello, my dog is cooler than you!", forward_params={"do_sample": True})
scipy.io.wavfile.write("bark_out.wav", rate=speech["sampling_rate"], data=speech["audio"])
```
3. Run inference via the Transformers modelling code. You can use the processor + generate code to convert text into a mono 24 kHz speech waveform for more fine-grained control.
```python
from transformers import AutoProcessor, AutoModel
processor = AutoProcessor.from_pretrained("suno/bark-small")
model = AutoModel.from_pretrained("suno/bark-small")
processor = AutoProcessor.from_pretrained("suno/bark")
model = AutoModel.from_pretrained("suno/bark")
inputs = processor(
text=["Hello, my name is Suno. And, uh — and I like pizza. [laughs] But I also have other interests such as playing tic tac toe."],
@ -95,7 +107,7 @@ inputs = processor(
speech_values = model.generate(**inputs, do_sample=True)
```
3. Listen to the speech samples either in an ipynb notebook:
4. Listen to the speech samples either in an ipynb notebook:
```python
from IPython.display import Audio
@ -121,7 +133,7 @@ You can also run Bark locally through the original [Bark library]((https://githu
1. First install the [`bark` library](https://github.com/suno-ai/bark)
3. Run the following Python code:
2. Run the following Python code:
```python
from bark import SAMPLE_RATE, generate_audio, preload_models