Instructions to use m-a-p/MERT-v1-330M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m-a-p/MERT-v1-330M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="m-a-p/MERT-v1-330M", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("m-a-p/MERT-v1-330M", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
passing device_map argument breaks the model
#6
by x75 - opened
Hi, I'm experimenting with MERT, thanks for making & providing it.
I noticed that whenever I am passing a "device_map" argument to AutoModel.from_pretrained the model only outputs nans. This happens regardless of the value of the argument, eg "cuda" or "cpu". When I remove the argument from the call, it works fine.
Initially observed on transformers==4.31.0, now I upgraded to 4.37.1 but its the same.
cheers