---
license: mit
task_categories:
- benchmarking
language:
- en
tags:
- llm
- scheduling
- control-plane
- benchmark
size_categories:
- n<1K
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: workload_id
    dtype: string
  - name: request_count
    dtype: int64
  - name: rate_per_second
    dtype: float64
  - name: arrival_pattern
    dtype: string
  - name: model_distribution
    struct:
    - name: Qwen/Qwen2.5-14B-Instruct
      dtype: float64
    - name: Qwen/Qwen2.5-7B-Instruct
      dtype: float64
    - name: meta-llama/Llama-3.1-8B-Instruct
      dtype: float64
    - name: mistralai/Mistral-7B-Instruct-v0.3
      dtype: float64
  - name: priority_distribution
    struct:
    - name: HIGH
      dtype: float64
    - name: LOW
      dtype: float64
    - name: NORMAL
      dtype: float64
  - name: prompt_len_range
    list: int64
  - name: output_len_range
    list: int64
  - name: slo_deadlines
    struct:
    - name: HIGH
      dtype: int64
    - name: LOW
      dtype: int64
    - name: NORMAL
      dtype: int64
  splits:
  - name: train
    num_bytes: 1021
    num_examples: 7
  download_size: 8744
  dataset_size: 1021
---

# SAGE Control Plane Workloads

Workload configurations for benchmarking Control Plane scheduling policies.

## Usage

```python
from datasets import load_dataset
workloads = load_dataset("intellistream/sage-control-plane-workloads")
```