Datasets:

vector-institute
/

dia-state-lab-2026

model_id string	has_report bool	parent_models string	relation string	updated_at string	scope string	energy_kwh_lo float64	energy_kwh_hi float64	carbon_kgco2eq_lo float64	carbon_kgco2eq_hi float64	water_liters_lo float64	water_liters_hi float64	energy_quality string	carbon_quality string	water_quality string	gpu string	gpu_count int64	gpu_hours float64	region string	tool string	method string
DIA-MVP/bert-tiny-sst2-distill	true	distilbert-base-uncased-finetuned-sst-2-english	distill	2026-07-08T19:07:06.623312+00:00	incremental	0.0015	0.0015	0	0	0.003	0.006	estimated-from-hardware	estimated-from-region	estimated-from-default-wue	NVIDIA A40	1	0.0063	ca-on	dia-track-estimate	distill
DIA-MVP/bert-tiny-sst2-distill-v2	true	DIA-MVP/bert-tiny-sst2-distill	distill	2026-07-08T20:34:28.571758+00:00	incremental	0.0007	0.0007	0	0	0.001	0.003	estimated-from-hardware	estimated-from-region	estimated-from-default-wue	NVIDIA A40	1	0.0031	ca-on	dia-track-estimate	distill
DIA-MVP/bert-tinybert-distill	true	distilbert-base-uncased-finetuned-sst-2-english	distill	2026-07-08T20:34:28.576741+00:00	incremental	0.0014	0.0014	0.0001	0.0001	0.002	0.005	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.0073	ca-on	codecarbon	distill
DIA-MVP/cifar10-simclr-a100	true	scratch	finetune	2026-07-08T19:07:06.167078+00:00	incremental	0.0105	0.0105	0.0007	0.0007	0.019	0.042	measured	measured	estimated-from-default-wue	NVIDIA A100-SXM4-80GB	1	0.0555	ca-on	codecarbon	finetune
DIA-MVP/cifar10-simclr-a40	true	scratch	finetune	2026-07-08T19:07:05.198205+00:00	incremental	0.0137	0.0137	0.0009	0.0009	0.025	0.055	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.0663	ca-on	codecarbon	finetune
DIA-MVP/cifar10-simclr-cpu	true	scratch	finetune	2026-07-08T19:07:05.996818+00:00	incremental	0.0066	0.0066	0.0004	0.0004	0.012	0.026	measured	measured	estimated-from-default-wue	cpu-80core	1	0.1366	ca-on	codecarbon	finetune
DIA-MVP/gemma-2b-lora	true	google/gemma-2-2b-it	lora	2026-07-08T20:34:28.583170+00:00	incremental	0.053	0.053	0.0034	0.0034	0.095	0.212	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.1642	ca-on	codecarbon	lora
DIA-MVP/llama31-8b-lora	true	meta-llama/Llama-3.1-8B-Instruct	lora	2026-07-08T19:07:06.815084+00:00	incremental	0.2024	0.2024	0.0061	0.0061	0.364	0.81	estimated-from-hardware	estimated-from-region	estimated-from-default-wue	NVIDIA A100-SXM4-80GB	1	0.6571	ca-on	dia-track-estimate	lora
DIA-MVP/llama32-3b-lora-a100	true	meta-llama/Llama-3.2-3B-Instruct	lora	2026-07-08T19:07:05.432609+00:00	incremental	0.1082	0.1082	0.007	0.007	0.195	0.433	measured	measured	estimated-from-default-wue	NVIDIA A100-SXM4-80GB	1	0.3014	ca-on	codecarbon	lora
DIA-MVP/measure-test-bert	true	distilbert-base-uncased	finetune	2026-07-08T19:20:58.976276+00:00	incremental	0.0059	0.0059	0.0004	0.0004	0.011	0.023	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.0219	ca-on	codecarbon	finetune
DIA-MVP/mnist-ddpm-a100	true	scratch	finetune	2026-07-08T19:07:06.274557+00:00	incremental	0.104	0.104	0.0067	0.0067	0.187	0.416	measured	measured	estimated-from-default-wue	NVIDIA A100-SXM4-80GB	1	0.5017	ca-on	codecarbon	finetune
DIA-MVP/mnist-ddpm-a40	true	scratch	finetune	2026-07-08T20:34:28.566700+00:00	incremental	0.0963	0.0963	0.0029	0.0029	0.173	0.385	estimated-from-hardware	estimated-from-region	estimated-from-default-wue	NVIDIA A40	1	0.4167	ca-on	dia-track-estimate	finetune
DIA-MVP/mnist-ddpm-cpu	true	scratch	finetune	2026-07-08T19:07:05.884995+00:00	incremental	0.0244	0.0244	0.0016	0.0016	0.044	0.098	measured	measured	estimated-from-default-wue	cpu-80core	1	0.502	ca-on	codecarbon	finetune
DIA-MVP/my-bert-sentiment-a100	true	distilbert-base-uncased	finetune	2026-07-08T19:07:05.573220+00:00	incremental	0.0049	0.0049	0.0003	0.0003	0.009	0.02	measured	measured	estimated-from-default-wue	NVIDIA A100-SXM4-80GB	1	0.017	ca-on	codecarbon	finetune
DIA-MVP/my-bert-sentiment-a40	true	distilbert-base-uncased	finetune	2026-07-08T19:07:05.048661+00:00	incremental	0.0061	0.0061	0.0004	0.0004	0.011	0.025	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.0233	ca-on	codecarbon	finetune
DIA-MVP/my-bert-sentiment-a40-v2	true	DIA-MVP/my-bert-sentiment-a40	finetune	2026-07-08T19:07:06.483542+00:00	incremental	0.0047	0.0047	0.0001	0.0001	0.009	0.019	estimated-from-hardware	estimated-from-region	estimated-from-default-wue	NVIDIA A40	1	0.0205	ca-on	dia-track-estimate	finetune
DIA-MVP/my-bert-sentiment-a40-v3	true	DIA-MVP/my-bert-sentiment-a40-v2	finetune	2026-07-08T20:34:28.526734+00:00	incremental	0.0059	0.0059	0.0004	0.0004	0.011	0.024	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.0217	ca-on	codecarbon	finetune
DIA-MVP/my-bert-sentiment-a40-v4	true	DIA-MVP/my-bert-sentiment-a40-v3	finetune	2026-07-08T20:34:28.531840+00:00	incremental	0.0058	0.0058	0.0004	0.0004	0.01	0.023	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.0216	ca-on	codecarbon	finetune
DIA-MVP/my-bert-sentiment-apsouth	true	distilbert-base-uncased	finetune	2026-07-08T20:34:28.536811+00:00	incremental	0.0059	0.0059	0.0004	0.0004	0.011	0.024	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.0217	ap-south-1	codecarbon	finetune
DIA-MVP/my-bert-sentiment-cabc	true	distilbert-base-uncased	finetune	2026-07-08T20:34:28.541743+00:00	incremental	0.006	0.006	0.0004	0.0004	0.011	0.024	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.0218	ca-bc	codecarbon	finetune
DIA-MVP/my-bert-sentiment-cpu	true	distilbert-base-uncased	finetune	2026-07-08T19:07:05.678820+00:00	incremental	0.026	0.026	0.0017	0.0017	0.047	0.104	measured	measured	estimated-from-default-wue	cpu-80core	1	0.5381	ca-on	codecarbon	finetune
DIA-MVP/my-bert-sentiment-euwest	true	distilbert-base-uncased	finetune	2026-07-08T20:34:28.546720+00:00	incremental	0.006	0.006	0.0004	0.0004	0.011	0.024	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.0218	eu-west-1	codecarbon	finetune
DIA-MVP/my-bert-sentiment-euwest-v2	true	DIA-MVP/my-bert-sentiment-euwest	finetune	2026-07-08T20:34:28.551706+00:00	incremental	0.006	0.006	0.0004	0.0004	0.011	0.024	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.0218	eu-west-1	codecarbon	finetune
DIA-MVP/my-bert-sentiment-useast	true	distilbert-base-uncased	finetune	2026-07-08T20:34:28.556692+00:00	incremental	0.0049	0.0049	0.002	0.002	0.009	0.02	estimated-from-hardware	estimated-from-region	estimated-from-default-wue	NVIDIA A40	1	0.0213	us-east-1	dia-track-estimate	finetune
DIA-MVP/my-bert-sentiment-uswest	true	distilbert-base-uncased	finetune	2026-07-08T19:07:06.416599+00:00	incremental	0.0049	0.0049	0.0022	0.0022	0.009	0.019	estimated-from-hardware	estimated-from-region	estimated-from-default-wue	NVIDIA A40	1	0.0211	us-midwest	dia-track-estimate	finetune
DIA-MVP/my-bert-sentiment-uswest-v2	true	DIA-MVP/my-bert-sentiment-uswest	finetune	2026-07-08T20:34:28.561739+00:00	incremental	0.006	0.006	0.0004	0.0004	0.011	0.024	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.0218	ca-on	codecarbon	finetune
DIA-MVP/phi3-mini-lora	true	microsoft/Phi-3-mini-4k-instruct	lora	2026-07-08T19:07:06.726214+00:00	incremental	0.0837	0.0837	0.0025	0.0025	0.151	0.335	estimated-from-hardware	estimated-from-region	estimated-from-default-wue	NVIDIA A40	1	0.3624	ca-on	dia-track-estimate	lora
DIA-MVP/phi3-mini-lora-v2	true	DIA-MVP/phi3-mini-lora,microsoft/Phi-3-mini-4k-instruct	lora,finetune	2026-07-08T20:34:28.589091+00:00	incremental	0.0498	0.0498	0.0015	0.0015	0.09	0.199	estimated-from-hardware	estimated-from-region	estimated-from-default-wue	NVIDIA A40	1	0.2154	ca-on	dia-track-estimate	lora
DIA-MVP/qwen2.5-7b-lora-a100	true	Qwen/Qwen2.5-7B	lora	2026-07-08T19:07:05.815926+00:00	incremental	0.6828	0.6828	0.0442	0.0442	1.229	2.731	measured	measured	estimated-from-default-wue	NVIDIA A100-SXM4-80GB	1	1.6199	ca-on	codecarbon	lora
DIA-MVP/resnet50-cifar100-1xa100	true	microsoft/resnet-50	finetune	2026-07-08T20:34:28.594117+00:00	incremental	0.1797	0.1797	0.0054	0.0054	0.323	0.719	estimated-from-hardware	estimated-from-region	estimated-from-default-wue	NVIDIA A100-SXM4-80GB	1	0.5834	ca-on	dia-track-estimate	finetune
DIA-MVP/resnet50-cifar100-2xa100	true	microsoft/resnet-50	finetune	2026-07-08T19:07:06.945446+00:00	incremental	0.4107	0.4107	0.0123	0.0123	0.739	1.643	estimated-from-hardware	estimated-from-region	estimated-from-default-wue	NVIDIA A100-SXM4-80GB	2	1.3334	ca-on	dia-track-estimate	finetune
DIA-MVP/resnet50-cifar100-a100	true	microsoft/resnet-50	finetune	2026-07-08T19:07:06.095140+00:00	incremental	0.1369	0.1369	0.0089	0.0089	0.246	0.548	measured	measured	estimated-from-default-wue	NVIDIA A100-SXM4-80GB	1	0.6684	ca-on	codecarbon	finetune
DIA-MVP/tinyllama-lora-a100	true	TinyLlama/TinyLlama-1.1B-Chat-v1.0	lora	2026-07-08T19:07:06.347456+00:00	incremental	0.0124	0.0124	0.0008	0.0008	0.022	0.05	measured	measured	estimated-from-default-wue	NVIDIA A100-SXM4-80GB	1	0.035	ca-on	codecarbon	lora
DIA-MVP/tinyllama-lora-a40	true	TinyLlama/TinyLlama-1.1B-Chat-v1.0	lora	2026-07-08T19:07:05.121043+00:00	incremental	0.0122	0.0122	0.0008	0.0008	0.022	0.049	measured	measured	estimated-from-default-wue	NVIDIA A40	1	0.0415	ca-on	codecarbon	lora
DIA-MVP/tinyllama-lora-a40-v2	true	DIA-MVP/tinyllama-lora-a40	lora	2026-07-08T19:07:06.552755+00:00	incremental	0.0089	0.0089	0.0003	0.0003	0.016	0.036	estimated-from-hardware	estimated-from-region	estimated-from-default-wue	NVIDIA A40	1	0.0386	ca-on	dia-track-estimate	lora
DIA-MVP/tinyllama-lora-cpu	true	TinyLlama/TinyLlama-1.1B-Chat-v1.0	lora	2026-07-08T19:07:05.746506+00:00	incremental	0.0515	0.0515	0.0033	0.0033	0.093	0.206	measured	measured	estimated-from-default-wue	cpu-80core	1	1.0613	ca-on	codecarbon	lora

DIA lab footprint table

This dataset is the rollup table for the Data & Impact Accounting (DIA) lab demo. It indexes the training footprint (energy, carbon, water) and lineage of a set of demo models trained across A100 / A40 / CPU hardware.

It is produced by ingesting each model's dia_report card and is read by the DIA Gradio dashboard. It stores metadata only — no model weights.

Files

nodes.parquet — one flat row per model (browsable in the Dataset Viewer): energy/carbon/water intervals, data-quality tier, GPU, GPU-hours, region, lineage.
state.json — the nested source of truth the dashboard loads.

How the rollup works

Given a base model, the dashboard builds the lineage as a directed graph and takes the base plus all its descendants as the family, then:

Sums incremental footprints — each model logs only its own training delta; the family total is the subtree sum.
Dedupes the DAG — a merged/shared model is counted once.
Reports coverage, not a bare total — totals are a lower bound at low disclosure.
Keeps provenance separate — measured vs estimated vs imputed.

Toolkit / paper: VectorInstitute/ai-impact-accounting
Models: the DIA-MVP/*-a100, *-a40, *-cpu repos ingested here.

Downloads last month: 151

Number of rows:

Total file size:

43.5 kB

Collection including vector-institute/dia-state-lab-2026

Data and Impact Accounting

Collection

Data and Impact Accounting (DIA) to track the carbon and water footprint of open-source AI and its derivatives. • 3 items • Updated 9 days ago

DIA lab footprint table

Files

How the rollup works

Related

Collection including vector-institute/dia-state-lab-2026