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library_name: peft
tags:
- dia
- carbon-footprint
- energy-efficiency
- sustainability
dia_report:
scope: incremental
lineage:
- model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
relation: lora
compute:
hardware:
gpu: NVIDIA A40
count: 1
duration_gpu_hours: 0.0415
footprint:
energy_kwh:
value: 0.0122
quality: measured
carbon_kgco2eq:
value: 0.0008
quality: measured
water_liters:
value:
- 0.022
- 0.049
quality: estimated-from-default-wue
context:
region: ca-on
carbon_intensity: 0.03
wue_l_per_kwh:
- 1.8
- 4.0
tool: codecarbon
dia_version: '0.1'
license: apache-2.0
pipeline_tag: text-generation
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
---
# TinyLlama 1.1B Chat — LoRA (NVIDIA A40)
A demo model from the **Data & Impact Accounting (DIA)** lab. It performs
instruction-tuning (LoRA adapter) via **LoRA (PEFT)**, with the base model `TinyLlama/TinyLlama-1.1B-Chat-v1.0`, trained on
**NVIDIA A40**.
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 A40 |
| Compute | 0.0415 GPU-hours |
| Energy | 0.0122 (measured) kWh |
| Carbon | 0.0008 (measured) kgCO₂eq |
| Water | 0.022–0.049 (estimated-from-default-wue) L |
| Grid region | ca-on |
*Energy and carbon are measured with [CodeCarbon](https://github.com/mlco2/codecarbon);
water is estimated from a default water-usage-effectiveness range. Carbon uses the
local grid's intensity (Ontario, ~0.03 kgCO₂eq/kWh).*
## Reproduce
```bash
REPO=DIA-MVP/tinyllama-lora-a40 python scripts/train_llama_lora.py
```
## Links
- **Footprint table (dataset):** [DIA-MVP/dia-state-lab-2026](https://huggingface.co/datasets/DIA-MVP/dia-state-lab-2026)
- **Project / paper:** [ai-impact-accounting](https://github.com/VectorInstitute/ai-impact-accounting)
- **Lab workflow:** see `LAB.md` in the repo
|