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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 706910d4036a9448ad122d5b698bc8d2d95835b9ffc250098f23e94e1f53e327
- Size of remote file:
- 415 MB
- SHA256:
- e210edaff81b0c23876722f10bb6fe49eb8ff237fa61f2fe81946da9010f2411
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