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
File size: 712 Bytes
fa61a60 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | {
"activation": "gelu",
"architectures": [
"UCEForExpressionPrediction"
],
"d_model": 512,
"decoder_dropout": 0.1,
"decoder_layer_dims": [
1024,
512,
512,
1
],
"dim_feedforward": 2048,
"dropout": 0.1,
"dtype": "float32",
"embedding_dim": 5120,
"embedding_init_path": null,
"embedding_reduction": "cls",
"embedding_requires_grad": false,
"expansion_factor": 4,
"max_sequence_length": 2048,
"model_type": "uce",
"nhead": 4,
"norm_first": false,
"num_layers": 8,
"output_embedding_dim": 512,
"padding_idx": 0,
"positional_encoding_type": "sinusoidal",
"transformers_version": "4.57.1",
"use_embedding_layer_norm": true,
"vocab_size": 145469
}
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