Tabular Classification
Transformers
Safetensors
felatab
feature-extraction
fela
tabular
in-context-learning
prior-fitted-network
foundation-model
delta-rule
cpu
on-device
custom_code
Eval Results (legacy)
Instructions to use lowdown-labs/fela-tab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lowdown-labs/fela-tab with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lowdown-labs/fela-tab", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "felatab", | |
| "library_name": "pytorch", | |
| "arch": "FelaTab", | |
| "tier": "small", | |
| "params_millions": 51.56, | |
| "max_features": 100, | |
| "max_classes": 10, | |
| "dim": 512, | |
| "n_layers": 14, | |
| "n_heads": 8, | |
| "head_dim": 64, | |
| "chunk": 64, | |
| "ffn_mult": 3, | |
| "use_landmark": true, | |
| "n_landmarks": 48, | |
| "ln_eps": 1e-05, | |
| "note": "Reads support rows (features plus label) then query rows; returns class probabilities or mean and std error bars." | |
| } | |