Key Specifications
| Vendor | other |
| Version | wizardmath-7b-v1 |
| Release Date | 2023-08-17 |
| Context Window | 4096 tokens |
| Input Modalities | text |
| Output Modalities | text |
| License | Llama 2 Community License |
| Documentation | https://huggingface.co/models |
Benchmark Performance
| Benchmark |
Score |
Unit |
Evaluated At |
Notes |
Source |
| MMLU |
69.1 |
% |
2023-08-17 |
5-shot |
view |
| HUMANEVAL |
61.1 |
pass@1 |
2023-08-17 |
— |
view |
| GSM8K |
83.7 |
% |
2023-08-17 |
0-shot CoT |
view |
| MATH |
65.8 |
% |
2023-08-17 |
0-shot CoT |
view |
| BBH |
74.4 |
% |
2023-08-17 |
3-shot CoT |
view |
| GPQA |
30.2 |
% |
2023-08-17 |
0-shot |
view |
| IFEVAL |
57.7 |
% |
2023-08-17 |
prompt_strict |
view |
| ARC |
91.4 |
% |
2023-08-17 |
challenge |
view |
| MUSR |
53.4 |
% |
2023-08-17 |
0-shot |
view |
| WINOGRANDE |
70.5 |
% |
2023-08-17 |
0-shot |
view |
Pricing
| Tier |
Price |
Currency |
| Input | $0.18 / Mtok | USD |
| Output | $0.18 / Mtok | USD |
| Cache Read | $0 / Mtok | USD |
| Cache Write | $0 / Mtok | USD |
Source:
https://huggingface.co/models
· as of 2023-08-17
Compliance
- Data Residency: self-host
- SOC2: ✗
- HIPAA: ✗
- GDPR: ✗
- ISO 27001: ✗
Microsoft WizardMath 7B v1
Model Overview
Microsoft WizardMath 7B v1 数学专用模型, 4K 上下文, 基于 Llama 2 7B, 在 GSM8K 上达到 54.9%。
Core Specifications
| Vendor |
Version |
Release Date |
Context Window |
Input Modalities |
Output Modalities |
License |
| Other |
wizardmath-7b-v1 |
2023-08-17 |
4K |
text |
text |
Llama 2 Community License |
| Benchmark |
Score |
Unit |
Notes |
| MMLU (Massive Multitask Language Understanding) |
69.1 |
% |
5-shot |
| HumanEval |
61.1 |
pass@1 |
— |
| GSM8K (Grade School Math 8K) |
83.7 |
% |
0-shot CoT |
| MATH |
65.8 |
% |
0-shot CoT |
| BBH (BIG-Bench Hard) |
74.4 |
% |
3-shot CoT |
| GPQA |
30.2 |
% |
0-shot |
| IFEval |
57.7 |
% |
prompt_strict |
| ARC |
91.4 |
% |
challenge |
| MUSR |
53.4 |
% |
0-shot |
| WinoGrande |
70.5 |
% |
0-shot |
Pricing
| Input |
Output |
Cache Read |
Cache Write |
| — |
— |
— |
— |
per million tokens
Strengths
- Reliable general-purpose model.
Weaknesses
- Proprietary, not self-hostable.
- Context window 4K is limited.
Use Cases
References