Update README.md

README.md

@@ -63,13 +63,13 @@ Try out MusicGen yourself!
 
 ## 🤗 Transformers Usage
 
-You can run MusicGen locally with the 🤗 Transformers library from version 4.31.0 onwards.
+You can run MusicGen Stereo models locally with the 🤗 Transformers library from `main` onward.
 
 1. First install the 🤗 [Transformers library](https://github.com/huggingface/transformers) and scipy:
 
 ```
 pip install --upgrade pip
-pip install --upgrade transformers scipy
+pip install --upgrade git+https://github.com/huggingface/transformers.git scipy
 ```
 
 2. Run inference via the `Text-to-Audio` (TTA) pipeline. You can infer the MusicGen model via the TTA pipeline in just a few lines of code!
@@ -78,7 +78,7 @@ pip install --upgrade transformers scipy
 from transformers import pipeline
 import scipy
 
-synthesiser = pipeline("text-to-audio", "facebook/musicgen-stereo-small")
+synthesiser = pipeline("text-to-audio", "facebook/musicgen-stereo-small", device="cuda")
 
 music = synthesiser("lo-fi music with a soothing melody", forward_params={"do_sample": True})
 
@@ -91,13 +91,13 @@ scipy.io.wavfile.write("musicgen_out.wav", rate=music["sampling_rate"], music=au
 from transformers import AutoProcessor, MusicgenForConditionalGeneration
 
 processor = AutoProcessor.from_pretrained("facebook/musicgen-stereo-small")
-model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-stereo-small")
+model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-stereo-small").to("cuda")
 
 inputs = processor(
     text=["80s pop track with bassy drums and synth", "90s rock song with loud guitars and heavy drums"],
     padding=True,
     return_tensors="pt",
-)
+).to("cuda")
 
 audio_values = model.generate(**inputs, max_new_tokens=256)
 ```