qwen2.5-7b-lora-a100

DIA-MVP/qwen2.5-7b-lora-a100

qwen2.5-7b-lora-a100 is a text generation model from DIA-MVP. Use it when you need the model to write or continue text. It is set up for peft. The card lists the license as apache-2.0.

A demo model from the Data & Impact Accounting (DIA) lab. It performs instruction-tuning (LoRA adapter) via LoRA (PEFT), with the base model Qwen/Qwen2.5-7B, trained on NVIDIA A100.

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.safetensors162 MB · 93%

At a glance

Task: Text Generation
Library: peft
License: apache-2.0
Access: Public
Created: Jun 29, 2026
Updated: Jun 29, 2026
SHA: d11246b4

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Base models

Qwen/Qwen2.5-7B

Model card

From the Hugging Face model README

Qwen2.5-7B — LoRA (NVIDIA A100)

A demo model from the Data & Impact Accounting (DIA) lab. It performs instruction-tuning (LoRA adapter) via LoRA (PEFT), with the base model Qwen/Qwen2.5-7B, trained on NVIDIA A100.

The point of this repo is not the model itself but its dia_report — a standardized record of the energy, carbon, and water used to train it, embedded in this card's metadata.

This footprint feeds the DIA dashboard, which rolls up a base model and all its derivatives to show the cumulative carbon, water, and energy cost of a model family.

Training footprint

Metric	Value
Hardware	1× NVIDIA A100-SXM4-80GB
Compute	1.6199 GPU-hours
Energy	0.6828 (measured) kWh
Carbon	0.0442 (measured) kgCO₂eq
Water	1.229–2.731 (estimated-from-default-wue) L
Grid region	ca-on

Energy and carbon are measured with CodeCarbon; water is estimated from a default water-usage-effectiveness range. Carbon uses the local grid's intensity (Ontario, ~0.03 kgCO₂eq/kWh).

Reproduce

REPO=DIA-MVP/qwen2.5-7b-lora-a100 python scripts/train_qwen_lora.py