Codesota · Models · Helium4 results · 4 benchmarks
Model card
Helium.
unknown
§ 02 · Benchmarks
Every benchmark Helium has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | Natural Questions | Natural Language Processing · Question Answering | accuracy | 23.3% | #4 | — | source ↗ |
| 02 | WinoGrande | Reasoning · Commonsense Reasoning | accuracy | 70.0% | #11 | — | source ↗ |
| 03 | HellaSwag | Reasoning · Commonsense Reasoning | accuracy | 76.3% | #12 | — | source ↗ |
| 04 | MMLU | Reasoning · Commonsense Reasoning | accuracy | 54.3% | #62 | — | source ↗ |
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 03 · Strengths by area
Where Helium actually performs.
§ 04 · Papers
1 paper with results for Helium.
- 2024-09-17· 4 results
Moshi: a speech-text foundation model for real-time dialogue
§ 06 · Sources & freshness
Where these numbers come from.
pwc-dump
4
results
0 of 4 rows marked verified.