Key Specifications
| Vendor | other |
|---|
| Version | yi-34b |
|---|
| Release Date | 2023-11-05 |
|---|
| Context Window | 4096 tokens |
|---|
| Input Modalities | text |
|---|
| Output Modalities | text |
|---|
| License | Apache 2.0 |
|---|
| Documentation | https://huggingface.co/models |
|---|
Benchmark Performance
| Benchmark | Score | Unit | Evaluated At | Notes | Source |
|---|
| MMLU | 55.5 | % | 2023-11-05 | 5-shot | view |
| HUMANEVAL | 35.8 | pass@1 | 2023-11-05 | — | view |
| GSM8K | 48.3 | % | 2023-11-05 | 0-shot CoT | view |
| MATH | 20.5 | % | 2023-11-05 | 0-shot CoT | view |
| BBH | 48.8 | % | 2023-11-05 | 3-shot CoT | view |
| GPQA | 20.6 | % | 2023-11-05 | 0-shot | view |
| IFEVAL | 48.2 | % | 2023-11-05 | prompt_strict | view |
| ARC | 87.2 | % | 2023-11-05 | challenge | view |
| MUSR | 36.8 | % | 2023-11-05 | 0-shot | view |
| WINOGRANDE | 71.5 | % | 2023-11-05 | 0-shot | view |
Pricing
| Tier | Price | Currency |
|---|
| Input | $0.4 / Mtok | USD |
| Output | $0.4 / Mtok | USD |
| Cache Read | $0 / Mtok | USD |
| Cache Write | $0 / Mtok | USD |
Source:
https://huggingface.co/models
· as of 2023-11-05
Compliance
- Data Residency: self-host
- SOC2: ✗
- HIPAA: ✗
- GDPR: ✗
- ISO 27001: ✗
Yi 34B
Model Genel Bakışı
01.AI Yi 34B 首代开源模型, 4K 上下文, 340 亿参数, 在开源模型中曾排名第一。
Temel Özellikler
| Satıcı | Sürüm | Yayın Tarihi | Bağlam Penceresi | Giriş Modları | Çıkış Modları | Lisans |
|---|
| Other | yi-34b | 2023-11-05 | 4K | text | text | Apache 2.0 |
| Benchmark | Puan | Birim | Notlar |
|---|
| MMLU (Massive Multitask Language Understanding) | 55.5 | % | 5-shot |
| HumanEval | 35.8 | pass@1 | — |
| GSM8K (Grade School Math 8K) | 48.3 | % | 0-shot CoT |
| MATH | 20.5 | % | 0-shot CoT |
| BBH (BIG-Bench Hard) | 48.8 | % | 3-shot CoT |
| GPQA | 20.6 | % | 0-shot |
| IFEval | 48.2 | % | prompt_strict |
| ARC | 87.2 | % | challenge |
| MUSR | 36.8 | % | 0-shot |
| WinoGrande | 71.5 | % | 0-shot |
Fiyatlandırma
| Giriş | Çıkış | Önbellek Okuma | Önbellek Yazma |
|---|
| — | — | — | — |
milyon token başına
Güçlü Yönler
Zayıf Yönler
- MMLU 仅 55.5,知识推理偏弱。
- HumanEval 35.8,代码能力较弱。
- 闭源专有模型,不支持自托管。
- 上下文窗口 4K 偏小。
Kullanım Senaryoları
Referanslar