Instructions to use KuanP/counts_flash_hog_4gpu_a6_long_u2_lowilr_bot75 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KuanP/counts_flash_hog_4gpu_a6_long_u2_lowilr_bot75 with Transformers:
# Load model directly from transformers import UCEForExpressionPrediction model = UCEForExpressionPrediction.from_pretrained("KuanP/counts_flash_hog_4gpu_a6_long_u2_lowilr_bot75", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "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, | |
| "input_projection_expansion_factor": 4, | |
| "input_projection_type": "linear", | |
| "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 | |
| } | |