Instructions to use KuanP/cxg-random75 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KuanP/cxg-random75 with Transformers:
# Load model directly from transformers import UCEForExpressionPrediction model = UCEForExpressionPrediction.from_pretrained("KuanP/cxg-random75", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload config.json with huggingface_hub
Browse files- config.json +33 -0
config.json
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{
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"activation": "gelu",
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"architectures": [
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"UCEForExpressionPrediction"
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],
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"d_model": 512,
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"decoder_dropout": 0.1,
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"decoder_layer_dims": [
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1024,
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512,
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512,
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1
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],
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"dim_feedforward": 2048,
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"dropout": 0.1,
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"dtype": "float32",
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"embedding_dim": 5120,
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"embedding_init_path": null,
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"embedding_reduction": "cls",
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"embedding_requires_grad": false,
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"expansion_factor": 4,
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"max_sequence_length": 2048,
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"model_type": "uce",
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"nhead": 4,
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"norm_first": false,
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"num_layers": 8,
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"output_embedding_dim": 512,
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"padding_idx": 0,
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"positional_encoding_type": "sinusoidal",
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"transformers_version": "4.57.1",
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"use_embedding_layer_norm": true,
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"vocab_size": 145469
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}
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