Instructions to use nqs-models/ising_fnqs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nqs-models/ising_fnqs with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nqs-models/ising_fnqs", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update vit_fnqs_model.py
Browse files- vit_fnqs_model.py +4 -4
vit_fnqs_model.py
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@@ -25,10 +25,10 @@ class ViTFNQSModel(FlaxPreTrainedModel):
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transl_invariant=config.tras_inv,
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two_dimensional=config.two_dim,
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)
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super().__init__(config, ViTFNQS, input_shape=input_shape, seed=seed, dtype=dtype, _do_init=_do_init)
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transl_invariant=config.tras_inv,
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two_dimensional=config.two_dim,
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)
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if not "return_z" in kwargs:
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self.return_z = False
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else:
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self.return_z = kwargs["return_z"]
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super().__init__(config, ViTFNQS, input_shape=input_shape, seed=seed, dtype=dtype, _do_init=_do_init)
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