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simple_nn
feature-extraction
finance
custom_code
Instructions to use yasinamp/simple_nn_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yasinamp/simple_nn_model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yasinamp/simple_nn_model", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| from transformers import PreTrainedModel | |
| import torch.nn as nn | |
| from .configuration_simple_model import SimpleNNConfig | |
| # Define the model class | |
| class SimpleNN(PreTrainedModel): | |
| config_class = SimpleNNConfig | |
| def __init__(self, config): | |
| super().__init__(config) | |
| self.dense = nn.Linear(config.input_size, config.num_classes) | |
| def forward(self, x): | |
| return self.dense(x) |