DIA-MVP
/

tinyllama-lora-cpu

@@ -1,6 +1,10 @@
 ---
-library_name: transformers
-tags: []
 dia_version: '0.1'
 dia_report:
   scope: incremental
@@ -31,199 +35,46 @@ dia_report:
     - 1.8
     - 4.0
   tool: codecarbon
 ---
-# Model Card for Model ID
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-## Model Details
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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 ---
+library_name: peft
+tags:
+- dia
+- carbon-footprint
+- energy-efficiency
+- sustainability
 dia_version: '0.1'
 dia_report:
   scope: incremental
     - 1.8
     - 4.0
   tool: codecarbon
+license: apache-2.0
+pipeline_tag: text-generation
+base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
 ---
+# TinyLlama 1.1B Chat — LoRA (CPU (80-core))
+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
+**CPU (80-core)**.
+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× cpu-80core |
+| Compute | 1.0613 GPU-hours |
+| Energy | 0.0515 (measured) kWh |
+| Carbon | 0.0033 (measured) kgCO₂eq |
+| Water | 0.093–0.206 (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-cpu 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