Instructions to use jncraton/DeepScaleR-1.5B-Preview-ct2-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jncraton/DeepScaleR-1.5B-Preview-ct2-int8 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jncraton/DeepScaleR-1.5B-Preview-ct2-int8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f9ec4bb13114418ae5e0d67dba72e9c85f671978a3382a202afdf02954aeb38
- Size of remote file:
- 1.78 GB
- SHA256:
- 69d294c56299d75e754b6fa90535cdef8ec0a7ca4cf79abd4141589c0ed975b5
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