Key Specifications
| Vendor | other |
|---|
| Version | yi-large |
|---|
| Release Date | 2024-05-13 |
|---|
| Context Window | 32768 tokens |
|---|
| Input Modalities | text |
|---|
| Output Modalities | text |
|---|
| License | Proprietary |
|---|
| Documentation | https://huggingface.co/models |
|---|
Benchmark Performance
| Benchmark | Score | Unit | Evaluated At | Notes | Source |
|---|
| MMLU | 82.8 | % | 2024-05-13 | 5-shot | view |
| HUMANEVAL | 72.2 | pass@1 | 2024-05-13 | — | view |
| GSM8K | 81.3 | % | 2024-05-13 | 0-shot CoT | view |
| MATH | 55.9 | % | 2024-05-13 | 0-shot CoT | view |
| BBH | 77.1 | % | 2024-05-13 | 3-shot CoT | view |
| GPQA | 35.2 | % | 2024-05-13 | 0-shot | view |
| IFEVAL | 73.4 | % | 2024-05-13 | prompt_strict | view |
| ARC | 94.8 | % | 2024-05-13 | challenge | view |
| MUSR | 59.4 | % | 2024-05-13 | 0-shot | view |
| WINOGRANDE | 84.1 | % | 2024-05-13 | 0-shot | view |
Pricing
| Tier | Price | Currency |
|---|
| Input | $3 / Mtok | USD |
| Output | $3 / Mtok | USD |
| Cache Read | $0 / Mtok | USD |
| Cache Write | $0 / Mtok | USD |
Source:
https://huggingface.co/models
· as of 2024-05-13
Compliance
- Data Residency: self-host
- SOC2: ✗
- HIPAA: ✗
- GDPR: ✗
- ISO 27001: ✗
Yi Large
Modellübersicht
01.AI Yi Large 旗舰闭源模型, 32K 上下文, 中英文能力突出, 在 LMSYS 排行榜上接近 GPT-4。
Kernspezifikationen
| Anbieter | Version | Veröffentlichungsdatum | Kontextfenster | Eingabemodalitäten | Ausgabemodalitäten | Lizenz |
|---|
| Other | yi-large | 2024-05-13 | 32K | text | text | Proprietary |
Benchmark-Leistung
| Benchmark | Ergebnis | Einheit | Notizen |
|---|
| MMLU (Massive Multitask Language Understanding) | 82.8 | % | 5-shot |
| HumanEval | 72.2 | pass@1 | — |
| GSM8K (Grade School Math 8K) | 81.3 | % | 0-shot CoT |
| MATH | 55.9 | % | 0-shot CoT |
| BBH (BIG-Bench Hard) | 77.1 | % | 3-shot CoT |
| GPQA | 35.2 | % | 0-shot |
| IFEval | 73.4 | % | prompt_strict |
| ARC | 94.8 | % | challenge |
| MUSR | 59.4 | % | 0-shot |
| WinoGrande | 84.1 | % | 0-shot |
Preise
| Eingabe | Ausgabe | Cache-Lesen | Cache-Schreiben |
|---|
| — | — | — | — |
pro Million Token
Stärken
- MMLU score 82.8, strong knowledge reasoning.
Schwächen
Anwendungsfälle
Referenzen