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DIA-MVP/tinyllama-lora-a40
tinyllama-lora-a40 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 TinyLlama/TinyLlama-1.1B-Chat-v1.0, trained on NVIDIA A40.
Downloads · 30 days
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From the Hugging Face model README
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.
| 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; water is estimated from a default water-usage-effectiveness range. Carbon uses the local grid's intensity (Ontario, ~0.03 kgCO₂eq/kWh).
REPO=DIA-MVP/tinyllama-lora-a40 python scripts/train_llama_lora.py
LAB.md in the repo