title: FelaTab playground
colorFrom: indigo
colorTo: green
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
license: other
FelaTab playground
Paste a small labelled table and a row to predict. FelaTab learns the pattern from your example rows in a single forward pass, with no training or setup, and fills the answer with a confidence range. Runs on CPU.
How to use
Put your data as comma or space separated rows, one row per line, with a header line. The last
column is the label. Use ? in the label column for the rows you want predicted.
- If the label column holds categories (e.g. Apple / Lemon / Grape), it predicts a class with probabilities (classification).
- If the label column holds numbers, it predicts a value with an error bar (regression).
Which model
The Space loads the small tier by default (dim512, about 51.6M parameters, int8, roughly 52 MB).
Set the environment variable FELATAB_TIER=big to load the flagship (about 411.9M parameters).
Honest scope
This is a research preview. FelaTab matches or slightly trails a tuned gradient boosted tree on zero shot classification and is behind trees on regression accuracy (it ships calibrated error bars for regression rather than headline accuracy). See the model card for the measured numbers.