Key Specifications
| Vendor | meta |
|---|
| Version | code-llama-70b |
|---|
| Release Date | 2024-01-29 |
|---|
| Context Window | 16000 tokens |
|---|
| Input Modalities | text |
|---|
| Output Modalities | text |
|---|
| License | Llama 2 Community License |
|---|
| Documentation | https://llama.meta.com/docs/ |
|---|
Benchmark Performance
| Benchmark | Score | Unit | Evaluated At | Notes | Source |
|---|
| MMLU | 62.1 | % | 2024-01-29 | 5-shot | view |
| HUMANEVAL | 65.6 | pass@1 | 2024-01-29 | — | view |
| GSM8K | 61 | % | 2024-01-29 | 0-shot CoT | view |
| MATH | 34 | % | 2024-01-29 | 0-shot CoT | view |
| BBH | 72.1 | % | 2024-01-29 | 3-shot CoT | view |
| GPQA | 25.3 | % | 2024-01-29 | 0-shot | view |
| IFEVAL | 63.8 | % | 2024-01-29 | prompt_strict | view |
| ARC | 89.8 | % | 2024-01-29 | challenge | view |
| MUSR | 40.1 | % | 2024-01-29 | 0-shot | view |
| WINOGRANDE | 75.5 | % | 2024-01-29 | 0-shot | view |
Pricing
| Tier | Price | Currency |
|---|
| Input | $0.9 / Mtok | USD |
| Output | $0.9 / Mtok | USD |
| Cache Read | $0 / Mtok | USD |
| Cache Write | $0 / Mtok | USD |
Source:
https://ai.meta.com/blog/
· as of 2024-01-29
Compliance
- Data Residency: self-host
- SOC2: ✗
- HIPAA: ✗
- GDPR: ✗
- ISO 27001: ✗
Code Llama 70B
Przegląd modelu
Meta Code Llama 70B 代码专用开源模型, 16K 上下文, 基于 Llama 2 微调, 支持多语言代码生成。
Podstawowe specyfikacje
| Dostawca | Wersja | Data wydania | Okno kontekstowe | Modalności wejściowe | Modalności wyjściowe | Licencja |
|---|
| Meta | code-llama-70b | 2024-01-29 | 16K | text | text | Llama 2 Community License |
Wydajność benchmarków
| Benchmark | Wynik | Jednostka | Uwagi |
|---|
| MMLU (Massive Multitask Language Understanding) | 62.1 | % | 5-shot |
| HumanEval | 65.6 | pass@1 | — |
| GSM8K (Grade School Math 8K) | 61.0 | % | 0-shot CoT |
| MATH | 34.0 | % | 0-shot CoT |
| BBH (BIG-Bench Hard) | 72.1 | % | 3-shot CoT |
| GPQA | 25.3 | % | 0-shot |
| IFEval | 63.8 | % | prompt_strict |
| ARC | 89.8 | % | challenge |
| MUSR | 40.1 | % | 0-shot |
| WinoGrande | 75.5 | % | 0-shot |
Ceny
| Wejście | Wyjście | Odczyt pamięci podręcznej | Zapis pamięci podręcznej |
|---|
| — | — | — | — |
za milion tokenów
Mocne strony
Słabe strony
- 闭源专有模型，不支持自托管。
- 上下文窗口 16K 偏小。
Przypadki użycia
Referencje