Key Specifications
| Vendor | other |
|---|
| Version | wizardcoder-python-34b |
|---|
| Release Date | 2023-08-17 |
|---|
| Context Window | 16384 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 | 60 | % | 2023-08-17 | 5-shot | view |
| HUMANEVAL | 79.8 | pass@1 | 2023-08-17 | — | view |
| GSM8K | 46.7 | % | 2023-08-17 | 0-shot CoT | view |
| MATH | 40.6 | % | 2023-08-17 | 0-shot CoT | view |
| BBH | 67.2 | % | 2023-08-17 | 3-shot CoT | view |
| GPQA | 36.6 | % | 2023-08-17 | 0-shot | view |
| IFEVAL | 53.8 | % | 2023-08-17 | prompt_strict | view |
| ARC | 91.2 | % | 2023-08-17 | challenge | view |
| MUSR | 53.1 | % | 2023-08-17 | 0-shot | view |
| WINOGRANDE | 70.4 | % | 2023-08-17 | 0-shot | view |
Pricing
| Tier | Price | Currency |
|---|
| Input | $0.5 / Mtok | USD |
| Output | $0.5 / 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 WizardCoder Python 34B
Descripción del modelo
Microsoft WizardCoder Python 34B 代码模型, 16K 上下文, 基于 Code Llama 34B, Python 代码生成突出。
Especificaciones principales
| Proveedor | Versión | Fecha de lanzamiento | Ventana de contexto | Modalidades de entrada | Modalidades de salida | Licencia |
|---|
| Other | wizardcoder-python-34b | 2023-08-17 | 16K | text | text | Llama 2 Community License |
Rendimiento en benchmarks
| Benchmark | Puntuación | Unidad | Notas |
|---|
| MMLU (Massive Multitask Language Understanding) | 60.0 | % | 5-shot |
| HumanEval | 79.8 | pass@1 | — |
| GSM8K (Grade School Math 8K) | 46.7 | % | 0-shot CoT |
| MATH | 40.6 | % | 0-shot CoT |
| BBH (BIG-Bench Hard) | 67.2 | % | 3-shot CoT |
| GPQA | 36.6 | % | 0-shot |
| IFEval | 53.8 | % | prompt_strict |
| ARC | 91.2 | % | challenge |
| MUSR | 53.1 | % | 0-shot |
| WinoGrande | 70.4 | % | 0-shot |
Precios
| Entrada | Salida | Lectura caché | Escritura caché |
|---|
| — | — | — | — |
por millón de tokens
Fortalezas
Debilidades
- 闭源专有模型，不支持自托管。
- 上下文窗口 16K 偏小。
Casos de uso
Referencias