Training model clause: Copy, customize, and use instantly
Introduction
A training model clause governs how machine learning or AI models themselves—not just the data—are handled under a contract. It outlines who owns the model, how it can be used, modified, or shared, and what restrictions apply to its training, deployment, or commercialization.
Below are templates for training model clauses tailored to different scenarios. Copy, customize, and insert them into your agreement.
Training model clause with exclusive ownership
This version grants full ownership of the model to one party.
All models developed or trained under this agreement, including their parameters, architecture, and weights, shall be the sole property of [Party A], regardless of which party conducted the training process.
Training model clause with joint ownership
This version allows shared control over the model.
Any model trained under this agreement using joint resources or contributions shall be jointly owned by both parties, with any future use or commercialization requiring mutual written consent.
Training model clause with licensing restrictions
This version limits downstream use.
Trained models may not be licensed, sublicensed, or transferred to any third party without the prior written approval of the party holding the IP rights to the model architecture and training outputs.
Training model clause with use-case limitation
This version confines how the model can be used.
The trained model may only be deployed for the specific purposes set out in this agreement and may not be repurposed, adapted, or integrated into other systems without written authorization.
Training model clause with retention and deletion requirement
This version requires model removal upon termination.
Upon expiration or termination of this agreement, the receiving party must delete any models, checkpoints, fine-tuned weights, or derivatives trained under this agreement, unless otherwise agreed in writing.
Training model clause with no transfer of pre-trained models
This version restricts access to base models.
Pre-trained or foundation models owned by either party prior to the effective date of this agreement shall remain the sole property of that party and shall not be transferred, copied, or accessed without separate licensing.
Training model clause with auditability obligation
This version ensures visibility into model internals.
Each party shall maintain detailed records of model architecture, hyperparameters, training configurations, and source code used, and shall provide such documentation to the other party upon request.
Training model clause with evaluation and validation rights
This version allows performance testing.
The disclosing party reserves the right to evaluate the performance, fairness, and security of any model trained using its data or infrastructure, and may request adjustments before deployment.
Training model clause with revenue share structure
This version allocates financial benefit.
If the trained model is commercialized, [Party A] shall receive [X]% of net revenues derived from its use, sale, or licensing, with payments to be made quarterly.
Training model clause with model deployment approval
This version prevents unauthorized release.
No trained model or derivative may be publicly deployed, published, or made available to third parties without the prior written approval of the model owner.
Training model clause with background IP protection
This version preserves pre-existing IP.
Each party retains full ownership of any model architecture, codebase, or intellectual property developed prior to or independently from this agreement, regardless of its use in model training.
Training model clause with commercial restriction
This version blocks model monetization.
Models trained under this agreement shall not be used in any commercial context, including but not limited to resale, licensing, or integration into paid services, without prior written approval.
Training model clause with open-source prohibition
This version restricts public release.
No party may release the trained model or any portion of it under an open-source license or into the public domain without the other party’s express written consent.
Training model clause with no third-party transfer
This version prevents model sharing.
Trained models may not be transferred, disclosed, or sublicensed to any third party, including affiliates, without the express written permission of the model owner.
Training model clause with architecture confidentiality
This version protects structural design.
The structure, configuration, and design of any models developed under this agreement shall be treated as confidential information and may not be disclosed without prior authorization.
Training model clause with retraining controls
This version limits further development.
Trained models may not be re-trained, fine-tuned, or otherwise modified using new datasets without the explicit written consent of the owning party.
Training model clause with audit trigger events
This version allows inspections based on conditions.
If a model is suspected of misuse, bias, or regulatory noncompliance, the disclosing party may trigger an independent audit of the model, including access to training logs and outputs.
Training model clause with inference-only licensing
This version restricts usage to predictions.
Any licensing of the trained model shall be limited to inference-only access. Licensees may not fine-tune, retrain, or modify the model in any way.
Training model clause with attribution requirement
This version mandates public credit.
Any public deployment, publication, or distribution of a model trained under this agreement must include attribution to the parties that contributed to its development.
Training model clause with warranty disclaimer
This version disclaims fitness of the model.
All models provided under this agreement are supplied “as is” without any warranties regarding accuracy, performance, or fitness for a particular purpose.
Training model clause with export control compliance
This version handles cross-border risks.
The parties agree not to export or make available trained models in jurisdictions where doing so would violate export control laws, sanctions, or trade restrictions.
Training model clause with explainability requirement
This version mandates transparency.
Models developed under this agreement must include features or documentation enabling explainability of model outputs in accordance with applicable regulatory standards.
Training model clause with bias testing protocol
This version ensures fairness.
Each model must undergo bias and fairness testing prior to deployment. Results must be shared with both parties, and any material issues must be mitigated before further use.
Training model clause with sandboxed testing rule
This version restricts initial model use.
All trained models must be deployed in a non-production sandbox environment until both parties confirm validation and security testing are complete.
Training model clause with version control obligation
This version mandates tracking.
All versions of models trained under this agreement must be stored with unique version identifiers, and each update must be documented, including date, changes, and training data used.
Training model clause with no reverse engineering
This version restricts architecture analysis.
Neither party may reverse engineer, decompile, or disassemble any model created by the other party under this agreement.
Training model clause with breach recovery mechanism
This version defines steps if terms are violated.
In the event of unauthorized model use, the responsible party shall immediately cease deployment, provide notice, and cooperate in mitigating potential harm or redistribution.
Training model clause with deployment limitation
This version restricts where the model can be hosted.
Trained models may only be deployed on infrastructure located within approved jurisdictions listed in Appendix A and may not be mirrored or hosted elsewhere.
Training model clause with intellectual property registration
This version clarifies IP filings.
Any intellectual property registrations or patent filings related to trained models must include both parties as co-inventors or contributors, unless otherwise agreed in writing.
Training model clause with derivative model rights
This version allocates control of modifications.
Any derivative models developed based on or using the original trained model shall be subject to the same licensing, usage, and ownership terms as the original.
Training model clause with benchmark testing consent
This version controls performance publicity.
Neither party shall use trained models for public benchmarks, competitions, or marketing comparisons without the other party’s written consent.
Training model clause with model escrow requirement
This version protects model access in emergencies.
The final trained model must be deposited in escrow with a neutral third party and may only be released under the terms outlined in Schedule B.
Training model clause with access tiering
This version limits user-level rights.
Access to the trained model must follow a tiered rights structure: administrative, read-only inference, and audit-only, with role-based restrictions enforced by the hosting platform.
Training model clause with pre-deployment checklist
This version enforces readiness review.
Before production deployment, the trained model must pass a formal checklist review, including security testing, fairness auditing, documentation, and rollback capability verification.
Training model clause with profit-sharing trigger
This version activates if the model is monetized.
If any revenue is derived from the trained model, the developing party shall allocate [X]% to the contributing party as profit share, payable quarterly.
Training model clause with deployment approval board
This version introduces a governance process.
Any production deployment of a trained model must be reviewed and approved by a joint model governance board composed of members from both parties.
Training model clause with open weights prohibition
This version keeps weights proprietary.
Under no circumstances shall the trained model’s weights be made publicly available or published in open repositories.
Training model clause with synthetic data training allowance
This version permits only synthetic inputs.
Models may only be trained on data synthesized or simulated for this agreement and must not include real-world user data unless separately approved.
Training model clause with commercialization hold
This version delays monetization.
The trained model may not be monetized for a period of [X] months after completion, allowing for additional review, audit, or adjustment.
Training model clause with interoperability standard
This version ensures platform flexibility.
Models trained under this agreement must be designed to operate across multiple platforms using standard model formats such as ONNX or TensorFlow SavedModel.
Training model clause with destruction certification
This version requires proof of model deletion.
If a trained model is deleted in accordance with this agreement, the party responsible shall provide written certification confirming complete and irreversible destruction of all model files, weights, and backups.
Training model clause with cloud provider restrictions
This version controls where models are hosted.
Trained models may only be deployed using cloud providers explicitly approved in writing by the disclosing party, and must comply with the same security obligations.
Training model clause with inference API limitation
This version restricts external exposure.
Trained models may not be exposed via public-facing APIs or endpoints unless they are secured behind authentication and authorized user access controls.
Training model clause with funding disclosure
This version requires financial transparency.
Any external funding received to support the training or development of models under this agreement must be disclosed in writing to the other party within ten (10) business days.
Training model clause with rollback protocol
This version requires backup for emergency recovery.
All trained models deployed in production must support rollback to a prior version in the event of performance degradation, data leakage, or ethical concern.
Training model clause with international transfer restrictions
This version limits cross-border movement.
The trained model and its associated components may not be exported, transferred, or shared with entities outside of [Country/Region] without express prior written consent.
Training model clause with post-deployment monitoring
This version ensures oversight of performance.
The deploying party agrees to monitor the trained model post-deployment for accuracy, bias, and drift, and will document all material changes over time.
Training model clause with licensing expiration
This version defines time limits for model use.
Any license to use a model trained under this agreement shall expire [X] months from the date of delivery unless renewed by mutual written agreement.
Training model clause with logging requirement
This version mandates recordkeeping.
All interactions with trained models, including inference queries and retraining events, must be logged and stored securely for a minimum of [X] months for auditing purposes.
Training model clause with independent validation rights
This version grants access to test accuracy.
Each party reserves the right to independently validate model performance, safety, and compliance using its own datasets and must be granted temporary testing access for that purpose.
Training model clause with carbon footprint tracking
This version adds environmental responsibility.
Each party agrees to document and disclose the environmental impact of training the model, including energy usage and carbon footprint where measurable.
Training model clause with non-production restriction
This version blocks customer-facing use.
Trained models may be used solely for internal testing and prototyping and may not be used in any customer-facing or external application.
Training model clause with explainability documentation
This version mandates interpretable model notes.
The developing party shall provide a summary of how the model makes predictions, including explanations of key features, decision paths, and risk scoring logic.
Training model clause with licensing fee floor
This version ensures minimum payment.
If licensed commercially, the trained model shall carry a minimum annual licensing fee of [$X], regardless of usage volume or model performance.
Training model clause with origin labeling requirement
This version requires metadata tagging.
Trained models must include metadata indicating the version, data sources used, training completion date, and responsible personnel for traceability purposes.
Training model clause with exclusive commercialization right
This version grants one party full profit rights.
[Party A] shall hold the exclusive right to commercialize any models trained under this agreement, including sales, licensing, or subscription access.
Training model clause with derivative disclosure duty
This version demands notice of extensions.
If a trained model is used to create a derivative, fine-tuned, or extended version, the originating party must be notified and may request technical details of the derivative model.
Training model clause with ethical board oversight
This version introduces governance review.
All models developed under this agreement must be reviewed and approved by a designated ethics committee before use in production or release.
Training model clause with performance SLA
This version ties usage to results.
The trained model must meet a minimum performance threshold of [X]% accuracy on a defined benchmark before being approved for deployment.
Training model clause with licensing termination trigger
This version defines auto-revocation.
Any breach of model usage restrictions shall immediately revoke any license granted for its use, and all further access to the trained model must be discontinued.
Training model clause with cybersecurity compliance
This version aligns with IT security standards.
Any system hosting the trained model must be compliant with cybersecurity standards such as NIST SP 800-53, ISO 27001, or equivalent as agreed by both parties.
Training model clause with no plug-in use
This version blocks extensions.
The trained model may not be extended through third-party plug-ins, wrappers, or adapters unless audited and approved by both parties in advance.
Training model clause with royalty structure
This version defines a per-use fee model.
For each paid use of the trained model by a third party, [Party A] shall remit a royalty of [$X] to [Party B], payable on a monthly basis with accompanying usage reports.
Training model clause with model degradation safeguard
This version watches for performance drop.
If the model demonstrates material degradation in output quality, accuracy, or fairness, the deploying party must temporarily disable the model and notify the originator.
Training model clause with reusability assessment
This version reviews model reuse scope.
Before applying a trained model to a new dataset or business domain, the party must assess whether the original training parameters remain valid and fair.
Training model clause with forensic audit rights
This version enables post-mortem review.
In the event of suspected misuse, the model originator shall have the right to request a forensic audit of the trained model and its associated logs, code, and configurations.
Training model clause with no public benchmarking
This version prevents performance bragging.
Trained models shall not be entered into public AI benchmarks, challenges, or press releases referencing performance without prior written approval.
Training model clause with competition exclusion
This version prohibits reverse development.
The trained model may not be used directly or indirectly to build a competing product, service, or internal tool that mimics its core functionality.
Training model clause with access expiration protocol
This version ends model access on termination.
All access credentials and API tokens to hosted models shall be revoked upon termination of this agreement, and all deployments must be deactivated within [X] days.
Training model clause with transfer-on-acquisition protection
This version handles M&A scenarios.
In the event of an acquisition, merger, or bankruptcy, the receiving party must notify the original model owner before transferring any rights to the trained model to the acquiring entity.
This article contains general legal information and does not contain legal advice. Cobrief is not a law firm or a substitute for an attorney or law firm. The law is complex and changes often. For legal advice, please ask a lawyer.