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:
# pip install -U transformers accelerate # 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
Commit History
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Upload benchmark/tabarena/SUBMISSION_DRAFT.md with huggingface_hub
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Upload benchmark/tabarena/ec2_run.sh with huggingface_hub
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wipe corrupt openml cache between phase retries
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12x600s phase retries (ride out OpenML outages)
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retry phases on transient failure
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fleet: spot/restore/checkpoint + systemd self-heal (launch_ec2.py)
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fleet: spot/restore/checkpoint + systemd self-heal (ec2_run.sh)
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v2: bagged config
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Update TabArena EC2 runner scripts (fela_ag_model.py)
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Update TabArena EC2 runner scripts (run_tabarena.py)
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Update TabArena EC2 runner scripts (ec2_run.sh)
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Update TabArena HF job scripts (run_tabarena.py)
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Update TabArena HF job script
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Update TabArena HF job script
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Document TabArena env requirements (separate AutoGluon venv)
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Remove stray pycache
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Add TabFM/GBM head-to-head benchmark, efficiency tables, and TabArena entry
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