datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DisPatch70AXXXX_jssp_policy_step_train_dispatch_v1nigerian_transport_and_logistics_warehouse_inventory_dispatch
Nigeria Transport & Logistics – Warehouse Inventory & Dispatch | Africa (Electric Sheep Africa metadata inventory)
Size category: 100K<n<1M - Formats: parquet - Sector: infrastructure_transport - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/nigerian_transport_and_logistics_warehouse_inventory_dispatch.model-categories
Model Categories
31 working models organized by use case.
🚀 dispatchAI
AXXXX_jssp_mixed_step_train_dispatch_v1cost-analysis
Cost Analysis
Cloud API vs on-device inference cost comparison.
At 10K queries/day: Save $18,249/year with on-device.
At 100K queries/day: Save $182,499/year.
🚀 dispatchAI
on-device-latency
On-Device Latency Benchmark
Real-world inference latency data for mobile-optimized LLMs, measured on actual phone hardware.
Hardware
Spec
Value
Device
Samsung S20 FE 5G
SoC
Snapdragon 865
RAM
8GB
OS
Android 13
Runtime
llama.cpp (4 threads)
Metrics
tokens_per_sec — Generation speed during inference
latency_ms_per_token — Time per generated token
ram_usage_mb — Peak RAM during inference
file_size_mb — GGUF model file size… See the full description on the dataset page: https://huggingface.co/datasets/dispatchAI/on-device-latency.hardware-profiles
Hardware Profiles
Phone hardware profiles for estimating mobile LLM inference speed.
Snapdragon 865 (Samsung S20 FE) is the verified baseline.
🚀 dispatchAI
speed-ranking
Speed Ranking
All 31 working dispatchAI models ranked by CPU inference speed.
🚀 dispatchAI
speed-benchmark
Speed Benchmark
CPU inference speed for all 22 verified dispatchAI models.
Measured with llama-cpp-python (8 threads, 512 context).
🚀 dispatchAI
all-verified-benchmarks
All Verified Benchmarks
Real CPU benchmark data for ALL 31 working dispatchAI models.
Zero broken models. Zero partial models. All verified.
🚀 dispatchAI
model-comparison
Model Comparison: Original vs Mobile
Shows the size reduction achieved by dispatchAI's re-engineering.
Model
Original
Mobile
Reduction
SmolLM2-135M
270MB
101MB
62.6%
Qwen2.5-0.5B
1000MB
469MB
53.1%
Llama-3.2-1B
2500MB
770MB
69.2%
🚀 dispatchAI
detailed-comparison
Detailed Comparison
Real verified data for all 31 working models. Includes speed-per-MB efficiency metric.
🚀 dispatchAI
dispatchr-grpo-runsefficiency-ranking
Efficiency Ranking
Models ranked by tokens-per-second per MB of file size. Higher = more efficient.
🚀 dispatchAI
data_fix_before_jssp_policy_step_train_dispatch_v1data_fix_before_jssp_mixed_step_train_dispatch_v1data_fix_before_jssp_reason_step_train_dispatch_v1jssp_policy_step_train_dispatch_v1jssp_policy_step_train_dispatch_v1