Instructions to use jdeschena/debug-tanh-mlp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jdeschena/debug-tanh-mlp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jdeschena/debug-tanh-mlp", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jdeschena/debug-tanh-mlp", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 325 Bytes
ef8e803 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"architectures": [
"MLPModel"
],
"auto_map": {
"AutoConfig": "configuration_mlp.MLPConfig",
"AutoModel": "modeling_mlp.MLPModel"
},
"dtype": "float32",
"hidden_dim": 32,
"input_dim": 16,
"model_type": "tanh_mlp",
"num_hidden_layers": 2,
"output_dim": 4,
"transformers_version": "5.13.0"
}
|