AI Model Licence

AI model licence and provenance clearance procedure

Status: publication hold
Last reviewed: 2026-08-03

Purpose and current decision

This document defines how RawCull clears the DataComp CLIP, OpenAI CLIP, and Meta SAM 3 model packs for public download. It covers technical provenance, licence evidence, upstream contacts, questions to ask, acceptable answers, and the final release gate.

No .aar model archive has been uploaded. Do not create a public GitHub Release, publish a download manifest, or change a production descriptor to ready until every model is either:

1. cleared under this procedure; or
2. deliberately excluded from the release and manifest.

The current AARs are unpublished development artifacts. The safest remedy for the recorded provenance gaps is to create new release candidates from pinned, hashed source files after the applicable licence has been cleared.

This is an engineering and evidence-preservation procedure, not legal advice. For an unresolved interpretation, obtain advice from a qualified lawyer who works with software copyright, open-source licensing, AI model weights, and commercial distribution in Norway and the EEA.

What “resolved” means

There are two independent gates.

Provenance gate

RawCull must be able to demonstrate this complete chain:

upstream owner and repository
        ↓
immutable revision and exact source-weight filename
        ↓
SHA-256 of the downloaded source file
        ↓
pinned conversion code, command, dependencies, and toolchain
        ↓
SHA-256 of the converted runtime model
        ↓
SHA-256 and byte size of the packaged AAR

A filename, a local cache timestamp, or a likely upstream snapshot is not a cryptographic binding. Re-exporting from a deliberately selected and hashed source is preferable to trying to infer the origin of an old conversion.

Licence and distribution gate

RawCull must have a defensible basis for all of the following:

• the licence applies to the exact trained weight file, not only source code;
• conversion into an Apple Core AI model is allowed;
• the converted derivative can be redistributed to third parties;
• the intended distribution can be public and commercial, if RawCull is commercially distributed;
• all notices, agreement copies, acceptance steps, use restrictions, and attribution requirements have been implemented; and
• a gated source checkpoint may be redistributed through RawCull’s proposed delivery mechanism, if applicable.

Silence, an unanswered ticket, a community member’s assumption, widespread third-party mirroring, or the technical ability to download a file does not resolve this gate. Prefer a written response from the model owner or an authorized representative. If that is unavailable, obtain a written opinion from qualified counsel or omit the model.

Current recorded evidence

The canonical records are:

• ModelAssets/Notices/CLIP-DataComp/PROVENANCE.json
• ModelAssets/Notices/CLIP-OpenAI/PROVENANCE.json
• ModelAssets/Notices/SAM3/PROVENANCE.json
• the licence and notice files beside each provenance record

The current relevant identifiers are:

These hashes identify current evidence; they do not themselves approve a release.

Common provenance remediation

Perform these steps separately for every model that passes its licence gate.

1. Choose one exact upstream repository, immutable commit, and source-weight file. Never use main, latest, an unpinned model alias, or an automatically changing download URL as the release input.
2. Download into a new, dated evidence directory. Preserve the upstream URL, immutable revision, filename, byte size, and SHA-256 before conversion.
3. Save the model card, licence or agreement, repository metadata, and any access terms as they appeared on the download date. Record their URLs and retrieval dates.
4. Record the converter repository and commit, Apple coreai-models commit, coreai-core version, Python environment or package lock, conversion command, macOS version, Xcode version, and conversion timestamp.
5. Run the conversion from that evidence directory. Do not allow the exporter to resolve or download a floating model identifier internally.
6. Hash the complete converted model directory with the established directory-tree-sha256-v1 method and hash its runtime main.mlirb file.
7. Validate the converted model with the same PhotoAIKit checks used by RawCull.
8. Update the corresponding PROVENANCE.json with the actual source revision, source filename, source SHA-256, conversion command or record, tool versions, output fingerprints, and supporting evidence references.
9. Rebuild the AAR using the explicit selectors. Verify that the chosen runtime model, tokenizer, metadata.json, and complete notice catalog are present, and that _source.aimodel and conversion intermediates are absent.
10. Record the new AAR byte size and SHA-256. The previous unpublished AAR hash must not be reused for the rebuilt archive.

An example pinned Hugging Face acquisition has this form; select the correct source filename before running it:

hf download OWNER/MODEL SOURCE_WEIGHT_FILE \
  --revision IMMUTABLE_COMMIT \
  --local-dir /path/to/private/release-evidence/MODEL/source

shasum -a 256 \
  /path/to/private/release-evidence/MODEL/source/SOURCE_WEIGHT_FILE

Keep raw correspondence, access tokens, account data, and legal advice out of the public repository. Store them in private, access-controlled records. A public provenance summary may record the response date, organization, scope, and internal evidence-record identifier without publishing personal data or privileged legal advice.

DataComp CLIP clearance

Current position

The pinned DataComp repository page identifies the checkpoint as MIT licensed, which is positive evidence. The remaining technical problem is that the existing exporter record does not identify and hash the exact source-weight file it converted.

Official references:

• Pinned DataComp checkpoint
• OpenCLIP repository
• LAION legal contact page

Who to contact

1. Email LAION at contact@laion.ai. LAION publishes this address on its official legal contact page.
2. Open a discussion on the exact Hugging Face model repository so the question and any maintainer response are tied to that checkpoint.
3. If necessary, open an issue with the OpenCLIP maintainers to identify which upstream file the datacomp_s34b_b86k configuration resolves. OpenCLIP can help with technical identity; the model owner or counsel should resolve licence scope.

Recorded LAION email request

On 2026-08-02 at 17:20 CEST, the RawCull maintainer emailed contact@laion.ai with the subject “Written clarification requested for DataComp CLIP weight licensing and redistribution.” The request identified:

• repository: laion/CLIP-ViT-B-32-256x256-DataComp-s34B-b86K;
• immutable revision: 4afec35ffe57a943d569ff7ee888061830164da8;
• proposed source-weight file: open_clip_model.safetensors;
• model configuration: OpenCLIP ViT-B-32-256 with datacomp_s34b_b86k weights;
• transformation: a float16 Apple Core AI runtime representation for local photo similarity and text-to-image semantic search; and
• delivery: an optional model archive downloaded by RawCull from a public GitHub Release, including possible use with a commercially distributed version of RawCull.

The email stated that RawCull has not publicly distributed the model or its converted derivative and will not redistribute the DataComp training dataset. It proposed preserving the source byte size and SHA-256 and including the applicable MIT licence, copyright and attribution notices, model information, provenance, and checksums with the archive.

LAION was asked to confirm whether the displayed MIT licence covers the exact weight file, conversion into the proposed runtime representation, public and commercial redistribution of the derivative, and whether any additional DataComp, OpenCLIP, attribution, acceptable-use, or other conditions apply. The request also asked whether the model card’s “out of scope” deployment language is safety guidance or an additional legal restriction.

Status: awaiting a substantive response from LAION or another person authorized to clarify the rights applicable to the weights. Sending the email does not clear the pack. Preserve the original message and any response in the private evidence register; do not add the maintainer’s personal email address or complete mail headers to this public repository.

Questions to ask

Identify the exact repository, revision, and proposed source file, then ask:

1. Is that exact trained weight file offered under the MIT licence shown on the model repository?
2. Does that permission cover conversion into another runtime representation and redistribution of the converted weights with a desktop application?
3. Is public and commercial redistribution permitted, provided the MIT notice is included?
4. Are any DataComp dataset terms, OpenCLIP terms, attribution requirements, or use restrictions additional to the displayed MIT licence applicable to the weight file?

Required technical work

1. Select exactly one of the upstream weight files rather than leaving the exporter to resolve a model alias.
2. Download it at revision 4afec35ffe57a943d569ff7ee888061830164da8 and record its SHA-256 and byte size.
3. Re-export DataComp CLIP from that local file under the common procedure.
4. Replace the null source revision and source checksum in ModelAssets/Notices/CLIP-DataComp/PROVENANCE.json.

Sufficient resolution

The pack may pass this gate when both conditions hold:

• the new conversion has a complete pinned-and-hashed provenance chain; and
• LAION or another demonstrably authorized model owner confirms the licence scope in writing, or qualified counsel concludes in writing that the repository’s MIT designation and accompanying materials are sufficient for the intended distribution.

If the answer is negative or remains materially ambiguous, replace the model with a checkpoint having explicit weight-level redistribution terms or omit the DataComp pack.

DataComp CLIP - no answer

If LAION does not provide a substantive answer after a documented follow-up, silence neither grants additional permission nor withdraws the permission already stated in the published materials. A release under the displayed MIT licence would rely on the public licence evidence rather than individualized clearance from LAION. Record it as a maintainer risk-acceptance decision, not as an upstream-approved or upstream-cleared release.

The evidence supporting that decision is:

• the exact pinned model repository identifies the model as License: mit and contains the weight files;
• Hugging Face’s licence documentation describes model-card licence metadata as communicating the permissions attributed to repository content; and
• the MIT licence permits use, modification, publication, redistribution, sublicensing, and sale when its copyright and permission notice accompanies copies or substantial portions.

The residual ambiguity is that the model repository has MIT metadata but no standalone LICENSE file identifying the trained weights and their copyright holder. The OpenCLIP MIT notice clearly covers the OpenCLIP software, but an unanswered inquiry leaves no individualized confirmation that it is also the intended notice for the trained weights and converted derivative. The model card’s “out of scope” deployment language appears as safety and intended-use guidance rather than licence text, but this interpretation has not been confirmed by LAION. Qualified Norwegian counsel remains the recommended way to resolve that ambiguity before a public or commercial release.

If the maintainer nevertheless decides to release without an answer, complete all of the following before publication:

1. Send and preserve one documented follow-up to LAION. Record the original request, follow-up date, response deadline, and absence of a substantive answer in the private evidence register.
2. Select open_clip_model.safetensors from revision 4afec35ffe57a943d569ff7ee888061830164da8 as the only conversion input. Its pinned Hugging Face metadata reports a byte size of 605189364 and SHA-256 92c26d60d3200ed5ed040dff31a8d19f8140648da8007216c25744c478deef27. Download the file independently and verify both values before conversion.
3. Re-export the Apple Core AI model from that pinned local file. Do not merely add the upstream hash to the provenance record for the existing conversion; the released derivative must be cryptographically tied to the verified source file.
4. Preserve dated copies of the pinned repository tree, model card, repository API metadata, MIT licence, OpenCLIP notice, conversion command, dependency versions, and all input and output checksums.
5. Package the complete applicable MIT copyright and permission notice, OpenCLIP and tokenizer notices, model card, safety limitations, provenance, and conversion information with every redistributed model archive. A link alone is not a substitute for including the required notice.
6. Keep DataComp CLIP identified as a separate third-party model asset. RawCull’s own MIT licence does not relicense the model, and RawCull must not claim ownership of or permission to redistribute the DataComp training dataset.
7. Complete the common provenance procedure, PhotoAIKit validation, AAR inspection, archive hashing, manifest verification, and download tests. Change PROVENANCE.json and the production catalogue to ready only after those technical controls describe the new release candidate accurately.
8. Add a signed and dated release decision stating the evidence relied upon, the unresolved licence ambiguity, whether RawCull is free or commercial, the intended distribution countries and channels, and the responsible maintainer’s acceptance of the residual risk.
9. Keep the model pack independently removable from the manifest and release so distribution can be suspended promptly if a credible rights claim or contrary clarification is received.

Releasing after these steps may provide a defensible MIT-compliance position, but it does not eliminate the residual legal risk created by the absence of a weight-specific licence file or an authorized response. This procedure records the evidence and decision; it is not a legal opinion.

OpenAI CLIP clearance

Current position

The OpenAI CLIP source repository contains an MIT licence covering the software and associated documentation. The Hugging Face checkpoint currently lacks a clear weight-level licence designation. A community discussion contains only an assumption that the repository licence covers the weights; that assumption is not authoritative evidence.

The model card also characterizes deployed uses as out of scope. Clarify whether this is safety guidance or an enforceable distribution/use condition, and independently assess RawCull’s use, testing, limitations, and disclosures.

Official references:

• OpenAI CLIP MIT licence
• OpenAI CLIP checkpoint
• Checkpoint licence discussion
• RawCull weight-licence clarification request
• OpenAI’s official support instructions
• CLIP model feedback form

Who to contact

1. Contact OpenAI Support using the chat control at help.openai.com. Ask that the request be routed to the team responsible for CLIP/open-source model licensing. Retain the ticket or conversation identifier.
2. Submit the same narrowly framed question through the feedback form linked by the official CLIP model card.
3. Open a model-specific discussion on the Hugging Face Community page using its New discussion action. This requires a Hugging Face login. Use a discussion rather than a pull request so the licensing question remains attached to the exact model distribution.
4. A response from an OpenAI employee or repository maintainer authorized to address the model’s licence is preferred. An unsupported answer from another community member is not sufficient.

GitHub issue creation for openai/CLIP is currently restricted, so it should not be the only planned contact route.

Recorded support outcome and Hugging Face escalation

OpenAI Support declined to confirm or provide an authoritative interpretation that the MIT licence in openai/CLIP applies to the pretrained weight files in openai/clip-vit-base-patch32. Support also declined to confirm that the licence permits RawCull’s intended commercial redistribution. The response said that the applicable terms must be determined from the licence and notices shipped with the exact code and weights being used.

This response does not clear the pack. Record the current conclusion as:

CLIP source code: MIT licensed.
openai/clip-vit-base-patch32 pretrained weights: no explicit weight-specific
licence identified in the downloaded distribution, and OpenAI Support did not
confirm that the source-repository MIT licence applies.
Commercial redistribution: unresolved and blocked pending sufficient evidence.

The OpenAI Report Content form is intended for reports of potentially illegal or policy-violating content. It is not evidence of permission and should not be treated as the route for prospective licensing clearance. Support’s recommended next step was to ask the maintainers on the distribution source. For Hugging Face, use the model-specific Community page linked above rather than the general Hugging Face forum.

On 2026-08-02, the RawCull maintainer opened Hugging Face discussion #72, “License applicable to pretrained CLIP ViT-B/32 weights,” asking the OpenAI maintainers to identify the licence covering the hosted weights and to confirm whether it permits commercial use and redistribution. The request also asks the maintainers to add the applicable licence identifier or licence file to the model repository. Opening the discussion records the escalation but does not clear the pack; retain the response and assess the responder’s authority and the scope of any answer before changing the release decision.

Suggested discussion title:

Licence applicable to pretrained CLIP ViT-B/32 weights

Suggested discussion body:

Could the OpenAI maintainers clarify the licence applicable specifically to
the pretrained weight files in openai/clip-vit-base-patch32?

In particular, does OpenAI intend the MIT License from the official
openai/CLIP repository to cover the original ViT-B/32 checkpoint and the
converted weight files hosted here, including commercial use, conversion to
another runtime representation, and redistribution subject to the MIT
conditions?

If so, could you add the applicable licence identifier and/or LICENSE file to
this model repository so downstream users can establish a reliable licensing
record?

A maintainer comment may clarify intent, but the strongest resolution is a licence file, model-card licence declaration, or written statement from the rights holder that expressly covers the exact weights and proposed use. Until then, do not approve commercial redistribution of this pack.

Questions to ask

Provide this exact identity:

• repository: openai/clip-vit-base-patch32;
• revision: 3d74acf9a28c67741b2f4f2ea7635f0aaf6f0268;
• file: pytorch_model.bin;
• SHA-256: a63082132ba4f97a80bea76823f544493bffa8082296d62d71581a4feff1576f.

Ask:

1. What licence governs this exact trained weight file?
2. Does the OpenAI CLIP MIT licence apply to it, or is there a separate licence or set of terms?
3. May RawCull convert the weights into an Apple Core AI representation and publicly redistribute that converted derivative as an optional desktop-app download, including in a commercial application?
4. Which copyright notice, attribution, model card, use limitation, or other terms must accompany the derivative?
5. Is the model card’s statement that deployed uses are out of scope guidance, or does OpenAI intend it as a legal restriction on deployment or redistribution?

Required technical work

After licence clearance, re-export from the exact local source file and revision above. Record the conversion command and bind the new output to the source SHA-256. Update the provenance record and rebuild the AAR.

Sufficient resolution

The pack may pass this gate only with:

• an authoritative written statement identifying terms that permit the exact intended conversion and redistribution; or
• a written legal opinion accepting a clearly documented alternative basis.

A response that merely restates the code repository’s MIT licence without addressing the trained weights is not sufficient. If OpenAI does not answer or the answer does not permit the proposed distribution, omit OpenAI CLIP or use a replacement checkpoint with explicit weight-level terms.

Meta SAM 3 clearance

Current position

The SAM License dated November 19, 2025 defines the trained weights as SAM Materials and grants rights to use, reproduce, distribute, modify, and create derivatives. Distribution must remain under that agreement and a copy of the agreement must accompany the materials. RawCull now packages the complete agreement and requires acceptance of its verified text.

The separate unresolved question arises because Meta’s official checkpoint is gated. The model page requires a user to log in and share contact information, and Meta’s repository instructs users to request access and authenticate before downloading. Hugging Face documents that a gated model’s authors control access. The licence text appears permissive about redistribution, but a public GitHub download would let downstream users obtain the derivative without going through Meta’s upstream access flow.

Official references:

• SAM 3 repository
• SAM 3 checkpoint and access gate
• SAM License
• Hugging Face gated-model documentation
• Meta Open Source contact

Who to contact

1. Email Meta Open Source at opensource@meta.com. Meta publishes this contact address on its official Open Source terms page. Ask that the request be routed to the SAM 3 model/licensing owner.
2. Open a narrowly scoped issue in facebookresearch/sam3 and/or a discussion on facebook/sam3. Link the public question from the private email so the project team can answer in its preferred channel.
3. Contact Hugging Face only for clarification of how its gate operates. Hugging Face is the hosting platform; its support cannot substitute for permission or interpretation from Meta as the model owner.
4. If Meta does not give a clear response, obtain a written opinion from qualified counsel or omit SAM 3 from public hosting.

Questions to ask Meta

Provide this exact identity and delivery proposal:

• repository: facebook/sam3;
• revision: 3c879f39826c281e95690f02c7821c4de09afae7;
• file: model.safetensors;
• SHA-256: 6d06f0a5f84e435071fe6603e61d0b4cc7b40e0d39d487cfd4d67d8cc11cc14a;
• transformation: float16 Apple Core AI derivative for local inference;
• delivery: optional RawCull Managed Background Asset from a public GitHub Release;
• licence handling: complete SAM License packaged with the derivative and explicit in-app acceptance tied to the licence-text SHA-256.

Ask:

1. Does section 1 of the SAM License permit this converted derivative to be distributed from a public, ungated GitHub Release?
2. Must every downstream RawCull user independently request access through Meta’s Hugging Face gate before receiving the converted derivative?
3. If downstream gating is required, what information and approval must RawCull collect, and may RawCull technically administer that gate?
4. Is packaging the complete agreement and requiring verified in-app acceptance sufficient to distribute under the same agreement?
5. Are there additional attribution, branding, reporting, geographic, trade control, or prohibited-use measures RawCull must implement?
6. Does the answer apply to both free and commercial distribution of RawCull?

Possible outcomes

Meta confirms public ungated redistribution. Preserve the response, comply with every stated condition, re-export from the pinned source, update the provenance record, and have counsel review any material ambiguity before release.

Meta requires each recipient to pass its gate. Do not publish SAM 3 as a public GitHub Release asset. Managed Background Assets with an anonymous public origin will not reproduce individualized Hugging Face approval. Omit SAM 3 or design a separate authenticated acquisition flow and review it independently.

Meta declines, gives an unclear answer, or does not respond. Keep SAM 3 blocked. Obtain a legal opinion or omit it. Do not treat the licence’s general redistribution wording as resolving a separately imposed access condition without an accountable decision.

Required technical work after clearance

Re-export from the recorded revision and model.safetensors SHA-256, recording the complete conversion command and environment. Preserve the full SAM License with the pack, maintain explicit acceptance against its checksum, and rebuild the AAR. Re-check the official licence immediately before publication because the agreement states that Meta may modify it.

Contact-request template

Use a real name and reply-capable address. Do not send an archive, proprietary source, access token, or confidential material unless the recipient requests it through an appropriate channel.

Subject: Written clarification requested for redistribution of [MODEL] in RawCull

Hello,

I maintain RawCull, a macOS photo-culling application:
https://github.com/rsyncOSX/RawCull

I have not published or uploaded the model derivative described below. I am
seeking written clarification before doing so.

Upstream repository: [URL]
Immutable revision: [COMMIT]
Source weight file: [FILENAME]
Source SHA-256: [SHA256]

RawCull converts this file to a float16 Apple Core AI model for local inference.
The proposed delivery is an optional Managed Background Asset downloaded from a
public GitHub Release. The archive will include the applicable complete licence,
notices, attribution, provenance, and checksums. [Describe explicit acceptance,
if applicable.] RawCull is [free/paid; choose the accurate description].

Please confirm:

1. Which licence or terms govern this exact trained weight file?
2. May it be converted into this runtime representation?
3. May the converted derivative be publicly redistributed in this manner,
   including as part of a commercial application if applicable?
4. What notices, acceptance flow, attribution, gating, use restrictions, or
   other conditions must RawCull implement?

I would appreciate a response from the model owner or a person authorized to
clarify its licensing and distribution conditions. If another team handles
this request, please route it or identify the correct contact.

Thank you,
[NAME]
[CONTACT DETAILS]

For SAM 3, append the six SAM-specific questions above. For OpenAI CLIP, append the exact question about whether the MIT licence covers the trained weights and whether the model card’s deployment language is guidance or a restriction. For DataComp, ask whether the repository’s MIT designation covers the exact selected file.

When to involve a lawyer

Engage a Norwegian lawyer before publication if any of these apply:

• the model owner does not answer;
• the answer is informal, conditional, or ambiguous;
• a licence permits redistribution but an upstream gate suggests a different access policy;
• commercial use, downstream acceptance, trade controls, prohibited uses, or indemnification requires interpretation;
• the responder’s authority to bind the rights holder is uncertain; or
• RawCull will distribute in multiple jurisdictions.

Look for counsel with experience in copyright, software and open-source licensing, technology transactions, AI model weights, EEA law, and US/EU trade controls. The Norwegian Bar Association member search can verify professional membership. The Norwegian Industrial Property Office also publishes guidance on choosing an IP adviser.

Give counsel a private evidence bundle containing:

• the exact model card and licence captured on the download date;
• upstream repository, revision, source filename, SHA-256, and download method;
• the conversion recipe and explanation of what the derivative contains;
• complete notice catalogs;
• every upstream response with message headers, dates, ticket IDs, and links;
• RawCull’s intended countries, free or paid status, distribution channels, end-user flow, and licence-acceptance UI; and
• the proposed GitHub release and Managed Background Assets architecture.

Ask for a written conclusion for each model covering conversion, redistribution, commercial use, notices, downstream terms, gating, and any required technical controls. Keep privileged advice private. Record only the resulting release decision and non-confidential obligations in the repository, unless counsel approves broader disclosure.

Evidence and decision record

Maintain a private register with at least these fields:

Do not mark a contact item complete merely because a message was sent. Record the actual answer and whether it addresses the exact file and proposed delivery.

Final release checklist

A pack can change from blocked to ready only when every applicable item is complete:

• Exact upstream owner, repository, immutable revision, and source file are recorded.
• Source byte size and SHA-256 were computed before conversion.
• The licence is captured from an official source and its checksum is recorded.
• The licence demonstrably covers the trained weights and converted derivative.
• Public and commercial redistribution is permitted for RawCull’s actual delivery model.
• Any gated-access question is answered by the owner or resolved by qualified counsel.
• All required notices, agreement copies, attribution, acceptance, and use controls are implemented.
• The model was re-exported from the pinned local source under a recorded command and environment.
• Converted output fingerprints and runtime hashes are recorded.
• PhotoAIKit validation passes.
• A new AAR was built with explicit selectors and inspected.
• The AAR byte size and SHA-256 are recorded.
• PROVENANCE.json, NOTICE.md, and the application catalogue agree.
• A responsible human has signed and dated the release decision.

If even one required item remains open, keep that pack blocked or omit it.

Publication sequence after clearance

RawCull’s current policy is to wait until all three model decisions are resolved. A decision to omit or replace a model counts as resolution only when it is documented and the omitted asset is absent from the manifest.

After the decisions are complete:

1. Re-export every approved model from its pinned and hashed source.
2. Update the notice catalogs and change only genuinely approved catalogue descriptors to ready.
3. Rebuild and inspect the AARs; record their new hashes and sizes.
4. Generate and inspect the self-hosted download manifest with a non-beta or corrected ba-package toolchain.
5. Create the dedicated RawCull-AI-Models release as a draft and upload only approved packs, their required remote asset names, the manifest, and public evidence.
6. Verify every URL, redirect, byte size, and checksum while authenticated to the draft if necessary.
7. Run download, acceptance, validation, removal, and licence-change tests against a non-production environment.
8. Publish the release only after a final human review confirms that the manifest contains no blocked model and all obligations are satisfied.

Official-source summary

The following sources were checked on 2026-08-02:

• LAION publishes contact@laion.ai on its legal contact page.
• OpenAI directs support requests through the chat control at help.openai.com, and the CLIP model card links its own feedback form.
• Meta Open Source publishes opensource@meta.com on its terms page, and recommends project issues as the normal support channel in its open-source guidance.
• Hugging Face explains that model authors control access to gated models.

Recheck all licence text, model-card metadata, gates, contacts, and official links immediately before release because they can change.