Instructions to use m-a-p/MERT-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m-a-p/MERT-v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="m-a-p/MERT-v0", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("m-a-p/MERT-v0", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30c71aeaa26a0414f71824d7361316ccb39018f641e72590262682fd8ac7ae77
- Size of remote file:
- 378 MB
- SHA256:
- c2a7110e46198f9a5c0b2e7db7722ed6ee340eaf77760326c46a5e855f15030d
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