Instructions to use jesbu1/robometer-4b-fft-armnet-tiled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jesbu1/robometer-4b-fft-armnet-tiled with Transformers:
# Load model directly from transformers import AutoProcessor, RBM processor = AutoProcessor.from_pretrained("jesbu1/robometer-4b-fft-armnet-tiled") model = RBM.from_pretrained("jesbu1/robometer-4b-fft-armnet-tiled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0dc31978129050fea4e1609c694262403784636c61f74bf2a3eea82746d2d53e
- Size of remote file:
- 5.2 kB
- SHA256:
- 13fdf452ce8baa965b41b7814da6edcefb4c35eef0515e57c34c73e3a90b5876
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