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Put models side by side.
What each one decides, how well calibrated it is, how fast it answers and what it costs to pull. Up to 4 at a time; the better value in each row is marked.
| Property | biplov/emo-en-lora-proper |
|---|---|
| Summary | Emotion · lora (English). Which emotion does the writer express? Fine-tuned from aac6fef/laya-mlx. |
| Decides | choice |
| Architecture | laya |
| Fine-tuned from | aac6fef/laya-mlx |
| License | apache-2.0 |
| Decision accuracy | 88.2% |
| Calibration error | 0.022 |
| Valid action rate | — |
| Median latency | 55 ms |
| p95 latency | 61.5 ms |
| Evaluation suite | Emotion (6 labels) |
| Latest version | 0.1.0 |
| Variants | encoder, tokenizer |
| Size of latest version | 807.0 MB |
| Files | 7 |
| Downloads | 0 |
| Stars | 0 |
| Tags | mlx |
| Updated | Sep 24, 2026 |