Dataset Viewer
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",
"value": "",
"AIO": true,
"NCAs": true,
"DPs": true,
"explanation": "The unique identifier for the model (e.g. Llama 3.1-405B), including identifiers for collections of models where applicable, and a list of publicly available versions."
},
"ModelAuthenticity": {
"description": "Evidence establishing provenance and authenticity (e.g. hash, URL endpoint)",
"value": "",
"AIO": true,
"NCAs": true,
"DPs": false,
"explanation": "Evidence that establishes the provenance and authenticity of the model (e.g. a secure hash if binaries are distributed, or the URL endpoint in the case of a service), where available."
},
"ReleaseDate": {
"description": "Date when the model was first released",
"value": "",
"AIO": true,
"NCAs": true,
"DPs": true,
"explanation": "Date when the model was first released through any distribution channel."
},
"UnionMarketReleaseDate": {
"description": "Date when the model was placed on the Union market",
"value": "",
"AIO": true,
"NCAs": true,
"DPs": true,
"explanation": "Date when the model was placed on the Union market."
},
"ModelDependencies": {
"description": "List of model dependencies or 'N/A'",
"value": [],
"AIO": true,
"NCAs": true,
"DPs": true,
"explanation": "If the model is the result of a modification or fine-tuning of one or more general-purpose AI models previously placed on the market, list those models. Otherwise write ‘N/A’."
}
}
|
{
"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": {
"description": "Description of key design specifications, rationale, and assumptions",
"value": "",
"AIO": true,
"NCAs": true,
"DPs": false,
"explanation": "A general description of the key design specifications of the model, including rationale and assumptions made, to provide basic insight into how the model was designed. [Recommended 100 words]."
},
"InputModalities": {
"description": "Supported input modalities and maximum input sizes",
"options": [
"Text",
"Images",
"Audio",
"Video",
"Other"
],
"selected": [],
"maxSizes": {
"Text": "",
"Images": "",
"Audio": "",
"Video": "",
"Other": ""
},
"AIO": true,
"NCAs": true,
"DPs": true,
"explanation": "Supported input modalities (Text, Images, Audio, Video, or Other). For each selected modality please include maximum input size or 'N/A' if not defined."
},
"OutputModalities": {
"description": "Supported output modalities and maximum output sizes",
"options": [
"Text",
"Images",
"Audio",
"Video",
"Other"
],
"selected": [],
"maxSizes": {
"Text": "",
"Images": "",
"Audio": "",
"Video": "",
"Other": ""
},
"AIO": true,
"NCAs": false,
"DPs": true,
"explanation": "Supported output modalities (Text, Images, Audio, Video, or Other). For each selected modality include maximum output size or 'N/A' if not defined."
},
"TotalModelSize": {
"description": "Total number of parameters and parameter range",
"value": "",
"ranges": [
"1—500M",
"500M—5B",
"5B—15B",
"15B—50B",
"50B—100B",
"100B—500B",
"500B—1T",
">1T"
],
"selectedRange": "",
"AIO": true,
"NCAs": false,
"DPs": false,
"explanation": "The total number of parameters of the model, recorded with at least two significant figures, and the range within which the total number of parameters falls."
}
}
|
{
"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"
],
"selected": [],
"AIO": true,
"NCAs": true,
"DPs": false,
"explanation": "A list of the methods of distribution (enterprise, subscription, API, IDEs, firmware, open-source, etc.) through which the model has been made available in the Union market, with access level details."
},
"DistributionChannelsForDPs": {
"description": "Methods of distribution available to downstream providers",
"options": [
"Enterprise/subscription software suites",
"Public/subscription API access",
"IDE/device-specific apps or firmware",
"Open-source repositories",
"Other"
],
"selected": [],
"AIO": false,
"NCAs": false,
"DPs": true,
"explanation": "List of the methods of distribution through which the model can be made available to downstream providers."
},
"License": {
"description": "Link or copy of model license(s)",
"value": "",
"AIO": true,
"NCAs": true,
"DPs": false,
"explanation": "A link to model license(s) (or provide upon request by the AIO) or indicate that no model license exists."
},
"LicenseForDPs": {
"description": "Types/categories of licenses for downstream use",
"options": [
"Free and open source",
"Less permissive (restricted use)",
"Proprietary",
"No license (access via terms of service)"
],
"selected": [],
"AIO": false,
"NCAs": false,
"DPs": true,
"explanation": "Types of licences for downstream use: open source, less permissive (restricted), proprietary, or absence of license (via terms of service)."
},
"AdditionalAssets": {
"description": "List of additional assets with access and licenses",
"options": [
"Training data",
"Processing code",
"Training code",
"Inference code",
"Evaluation code",
"Other"
],
"selected": [],
"AIO": true,
"NCAs": false,
"DPs": true,
"explanation": "A list of additional assets (e.g. training data, training/inference code, evaluation code) that are made available, with details of how to access them and related licenses."
}
}
|
{
"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."
},
"IntendedUses": {
"description": "Description of intended and restricted uses",
"value": "",
"AIO": true,
"NCAs": true,
"DPs": true,
"explanation": "A description of intended or restricted uses as specified in instructions for use, terms and conditions, promotional materials, or technical documentation. [Recommended 200 words]."
},
"IntegrationTypes": {
"description": "AI systems in which model can/cannot be integrated",
"examples": [
"Autonomous systems",
"Conversational assistants",
"Decision support systems",
"Creative AI systems",
"Predictive systems",
"Cybersecurity",
"Surveillance",
"Human-AI collaboration"
],
"selected": [],
"AIO": true,
"NCAs": true,
"DPs": true,
"explanation": "Type and nature of AI systems in which the model can/cannot be integrated, e.g. autonomous systems, assistants, predictive systems. [Recommended 300 words]."
},
"TechnicalMeansForIntegration": {
"description": "Technical means required for model integration",
"value": "",
"AIO": false,
"NCAs": false,
"DPs": true,
"explanation": "A general description of the technical means (instructions, infrastructure, tools) required for integration into AI systems. [Recommended 100 words]."
},
"RequiredHardware": {
"description": "Hardware requirements (if any)",
"value": "",
"AIO": false,
"NCAs": false,
"DPs": true,
"explanation": "Description of hardware required to use the model, or 'N/A' if not applicable (e.g. API access). [Recommended 100 words]."
},
"RequiredSoftware": {
"description": "Software requirements (if any)",
"value": "",
"AIO": false,
"NCAs": false,
"DPs": true,
"explanation": "Description of software required to use the model, or 'N/A' if not applicable. [Recommended 100 words]."
}
}
|
{
"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, testing, and validation (Text, Images, Audio, Video, or Other)."
},
"DataProvenance": {
"description": "Sources of data",
"options": [
"Web crawling",
"Private third-party datasets",
"User data",
"Publicly available datasets",
"Other collected data",
"Synthetic data (non-public)"
],
"selected": [],
"AIO": true,
"NCAs": true,
"DPs": true,
"explanation": "Sources of data (Web crawl, private datasets, user data, public datasets, synthetic, or other)."
},
"NumberOfDataPoints": {
"description": "Size of datasets with units and required precision",
"training": "",
"testing": "",
"validation": "",
"unit": "",
"precision": [
"≥1 sig fig",
"≥2 sig fig"
],
"AIO": true,
"NCAs": true,
"DPs": false,
"explanation": "The size of the datasets (training, testing, validation) with definition of the unit of data points (e.g. tokens, documents, images, hours of video), recorded with required precision."
}
}
|
{
"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,
"explanation": "Duration of training measured either as a range (<1 month, 1–3 months, 3–6 months, >6 months) or precisely in wall clock days and hardware days."
},
"ComputationUsed": {
"description": "Amount of computation used for training",
"value": "",
"precision": [
"Order of magnitude",
"≥2 sig fig"
],
"AIO": true,
"NCAs": true,
"DPs": false,
"explanation": "Measured or estimated amount of computation used for training, reported in FLOPs (order of magnitude or ≥2 significant figures)."
}
}
|
{
"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."
},
"InferenceComputation": {
"description": "Benchmarked computation for inference (FLOPs)",
"value": "",
"precision": "≥2 sig fig",
"AIO": true,
"NCAs": true,
"DPs": false,
"explanation": "Benchmarked computation for inference, reported in FLOPs with ≥2 significant figures."
}
}
|
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:
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