GeneralInformation dict | ModelProperties dict | DistributionAndLicenses dict | Use dict | TrainingData dict | ComputationalResources dict | EnergyConsumption dict |
|---|---|---|---|---|---|---|
{
"LegalNameProvider": {
"description": "Legal name for the model provider",
"value": "",
"AIO": true,
"NCAs": true,
"DPs": true,
"explanation": "Legal name for the model provider."
},
"ModelName": {
"description": "Unique identifier for the model and publicly available versions",
... | {
"Architecture": {
"description": "General description of the model architecture",
"value": "",
"AIO": true,
"NCAs": true,
"DPs": true,
"explanation": "A general description of the model architecture, e.g. a transformer architecture. [Recommended 20 words]."
},
"DesignSpecifications": {
... | {
"DistributionChannels": {
"description": "List of methods of distribution with access levels",
"options": [
"Enterprise/subscription software suites",
"Public/subscription API access",
"IDE/device-specific apps or firmware",
"Open-source repositories",
"Other"
],
"selec... | {
"AcceptableUsePolicy": {
"description": "Link to acceptable use policy or statement that none exists",
"value": "",
"AIO": true,
"NCAs": true,
"DPs": true,
"explanation": "Provide a link to the acceptable use policy (or attach to the document) or indicate that none exists."
},
"IntendedU... | {
"DataType": {
"description": "Types/modalities of training, testing, validation data",
"options": [
"Text",
"Images",
"Audio",
"Video",
"Other"
],
"selected": [],
"AIO": true,
"NCAs": true,
"DPs": true,
"explanation": "Modalities of data used in training... | {
"TrainingTime": {
"description": "Training duration",
"ranges": [
"<1 month",
"1–3 months",
"3–6 months",
">6 months"
],
"selectedRange": "",
"precise": {
"wallClockDays": "",
"hardwareDays": ""
},
"AIO": true,
"NCAs": true,
"DPs": false,
"... | {
"TrainingEnergy": {
"description": "Energy used for training (MWh)",
"value": "",
"precision": "≥2 sig fig",
"AIO": true,
"NCAs": true,
"DPs": false,
"explanation": "Measured or estimated energy used for training (MWh), recorded with ≥2 significant figures. Enter ‘N/A’ if not estimable."... |
Based on The General-Purpose AI Code of Practice
Author: [AdrianGonzalezSanchez] (https://huggingface.co/AdrianGonzalezSanchez)
Original DOC TEMPLATE >>> Model_Documentation_Form.docx
Original PDF CHAPTER >>> Code_of_Practice_for_GeneralPurpose_AI_Models_Transparency_Chapter.pdf
Model Documentation JSON Schema
JSON FILE >>> GPAI_spec.json
This JSON file defines a structured schema for documenting general-purpose AI models in alignment with the EU AI Act transparency requirements. It mirrors the official Model Documentation Form template, with each row represented as a JSON field. Each entry contains:
- description → short explanation of what the field is asking for.
- value or selected → a placeholder for providers to fill in.
- options → enumerated choices where applicable (e.g. parameter ranges, data types, distribution channels).
- AIO / NCAs / DPs → Boolean flags showing which stakeholders the information is intended for:
- AIO = AI Office
- NCAs = National Competent Authorities
- DPs = Downstream Providers
- AIO / NCAs / DPs → Boolean flags showing which stakeholders the information is intended for:
- Downloads last month
- 5