Image Medium : documents, crédits, licence, provenance et manifeste

Fichiers d'exécution copiés depuis black-forest-labs/FLUX.2-klein-4B@e7b7dc27f91deacad38e78976d1f2b499d76a294. Ajout de README-source.md, licences, CREDITS, SOURCE.json et du manifeste.

.optima-package.json

@@ -92,6 +92,36 @@
       "path": "vae/diffusion_pytorch_model.safetensors",
       "sizeBytes": 168120878,
       "sha256": "ca70d2202afe6415bdbcb8793ba8cd99fd159cfe6192381504d6c4d3036e0f04"
+    },
+    {
+      "path": "CREDITS.json",
+      "sizeBytes": 2973,
+      "sha256": "0f69507cbdba3186e4672bf8b2a0efe31f7ce716d458121c31dda5b08e43219a"
+    },
+    {
+      "path": "CREDITS.md",
+      "sizeBytes": 2416,
+      "sha256": "1aa002dc9c8e81ea82b6923ae78c1b56cdec20f51d72ad3ed4dee6a1fe62efb2"
+    },
+    {
+      "path": "LICENSE",
+      "sizeBytes": 11358,
+      "sha256": "cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30"
+    },
+    {
+      "path": "LICENSE.md",
+      "sizeBytes": 9584,
+      "sha256": "ca02bc51900ab07789d1b70283329e7137f5af98f5161c23a1c81fc38a4af1fe"
+    },
+    {
+      "path": "README-source.md",
+      "sizeBytes": 9991,
+      "sha256": "bd447051cf2db4bf67b992e563d89c35ebf1123f009c063361a222ab14e1c4f7"
+    },
+    {
+      "path": "SOURCE.json",
+      "sizeBytes": 11121,
+      "sha256": "3990e4ea667530840cc4b425856b98ebb4591c513c6f8aaac393a6bdefe71756"
     }
   ]
 }

CREDITS.json

@@ -0,0 +1,90 @@
+{
+  "schemaVersion": 1,
+  "preparedAt": "2026-10-27T20:56:07.611Z",
+  "package": {
+    "id": "image.medium",
+    "repository": "optima-tools-ch/image-medium",
+    "label": "Génération d'images — Medium"
+  },
+  "model": {
+    "name": "FLUX.2 [klein] 4B — pipeline Diffusers",
+    "source": "black-forest-labs/FLUX.2-klein-4B",
+    "revision": "e7b7dc27f91deacad38e78976d1f2b499d76a294",
+    "url": "https://huggingface.co/black-forest-labs/FLUX.2-klein-4B/tree/e7b7dc27f91deacad38e78976d1f2b499d76a294"
+  },
+  "authors": [
+    {
+      "name": "Black Forest Labs",
+      "url": "https://bfl.ai/blog/flux2-klein-towards-interactive-visual-intelligence",
+      "role": "éditeur du modèle et propriétaire du dépôt source ; billet cité par la fiche source"
+    }
+  ],
+  "components": [
+    {
+      "folder": "scheduler",
+      "className": "FlowMatchEulerDiscreteScheduler"
+    },
+    {
+      "folder": "text_encoder",
+      "className": "Qwen3ForCausalLM",
+      "note": "classe indiquée par model_index.json ; la fiche source ne détaille pas son origine"
+    },
+    {
+      "folder": "tokenizer",
+      "className": "Qwen2TokenizerFast"
+    },
+    {
+      "folder": "transformer",
+      "className": "Flux2Transformer2DModel",
+      "note": "4 milliards de paramètres selon la fiche source"
+    },
+    {
+      "folder": "vae",
+      "className": "AutoencoderKLFlux2"
+    }
+  ],
+  "upstream": [],
+  "license": {
+    "spdx": "Apache-2.0",
+    "name": "Apache License 2.0",
+    "url": "https://www.apache.org/licenses/LICENSE-2.0.txt",
+    "files": [
+      "LICENSE",
+      "LICENSE.md"
+    ]
+  },
+  "licenseNotes": [
+    "La fiche source déclare Apache 2.0 (« Fully open under Apache 2.0 ») et fournit `LICENSE.md` : conditions de la licence Apache 2.0 sans annexe ni avis de copyright. Ce fichier est conservé tel quel.",
+    "Le texte officiel complet (avec annexe) est ajouté dans `LICENSE`.",
+    "La fiche source ne déclare aucune licence distincte pour les composants du pipeline (encodeur de texte de type Qwen3, VAE) ; Optima Tools n’en a évalué aucune autre."
+  ],
+  "copyrightNotices": [],
+  "preparedAndDistributedBy": {
+    "name": "Optima Tools",
+    "organization": "optima-tools-ch",
+    "role": "Préparateur et distributeur du paquet"
+  },
+  "modifications": {
+    "weights": "Aucune : octets identiques à ceux de la source, noms et arborescence conservés.",
+    "renamedFiles": [],
+    "addedDocuments": [
+      "README.md",
+      "README-source.md (copie)",
+      "LICENSE (texte officiel Apache 2.0)",
+      "CREDITS.md",
+      "CREDITS.json",
+      "SOURCE.json",
+      ".optima-package.json"
+    ]
+  },
+  "notCopiedFromSource": [
+    {
+      "path": "flux-2-klein-4b.safetensors",
+      "reason": "fichier autonome qui dupliquerait le poids du transformeur déjà livré dans transformer/"
+    },
+    {
+      "path": "editing.jpg, others.jpg, realism.jpg",
+      "reason": "images d’illustration de la fiche source"
+    }
+  ]
+}

CREDITS.md

@@ -0,0 +1,41 @@
+# Crédits — Optima Tools — Génération d'images — Medium
+
+## Modèle
+
+- **Nom :** FLUX.2 [klein] 4B — pipeline Diffusers. Identifiant du paquet OT : `image.medium`.
+- **Dépôt source :** https://huggingface.co/black-forest-labs/FLUX.2-klein-4B
+- **Révision source :** `e7b7dc27f91deacad38e78976d1f2b499d76a294` (https://huggingface.co/black-forest-labs/FLUX.2-klein-4B/tree/e7b7dc27f91deacad38e78976d1f2b499d76a294)
+
+## Auteurs
+
+- Black Forest Labs (éditeur du modèle et propriétaire du dépôt source ; billet cité par la fiche source) — https://bfl.ai/blog/flux2-klein-towards-interactive-visual-intelligence
+
+## Composants du pipeline
+
+- `scheduler` : FlowMatchEulerDiscreteScheduler
+- `text_encoder` : Qwen3ForCausalLM — classe indiquée par model_index.json ; la fiche source ne détaille pas son origine
+- `tokenizer` : Qwen2TokenizerFast
+- `transformer` : Flux2Transformer2DModel — 4 milliards de paramètres selon la fiche source
+- `vae` : AutoencoderKLFlux2
+
+## Licence
+
+- **Apache License 2.0** (Apache-2.0) : https://www.apache.org/licenses/LICENSE-2.0.txt
+- La fiche source déclare Apache 2.0 (« Fully open under Apache 2.0 ») et fournit `LICENSE.md` : conditions de la licence Apache 2.0 sans annexe ni avis de copyright. Ce fichier est conservé tel quel.
+- Le texte officiel complet (avec annexe) est ajouté dans `LICENSE`.
+- La fiche source ne déclare aucune licence distincte pour les composants du pipeline (encodeur de texte de type Qwen3, VAE) ; Optima Tools n’en a évalué aucune autre.
+- **Avis de copyright :** aucun avis de copyright reproductible n’est présent dans la source ; aucun n’est ajouté ici.
+
+## Préparation et distribution
+
+Ce paquet est préparé et distribué par **Optima Tools** (organisation `optima-tools-ch`). Optima Tools n'est pas l'auteur du modèle : les auteurs d'origine conservent leurs droits.
+
+## Modifications
+
+- **Poids :** Aucune : octets identiques à ceux de la source, noms et arborescence conservés.
+- **Ajouts d'Optima Tools :** `README.md`, `CREDITS.md`, `CREDITS.json`, `SOURCE.json`, `.optima-package.json`, `LICENSE`. `README-source.md` est la copie de la fiche officielle.
+
+## Non repris de la source
+
+- `flux-2-klein-4b.safetensors` : fichier autonome qui dupliquerait le poids du transformeur déjà livré dans transformer/
+- `editing.jpg, others.jpg, realism.jpg` : images d’illustration de la fiche source

LICENSE

@@ -0,0 +1,202 @@
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README-source.md

@@ -0,0 +1,125 @@
+---
+license: apache-2.0
+language:
+- en
+pipeline_tag: image-to-image
+tags:
+- text-to-image
+- image-editing
+- flux
+- diffusion-single-file
+---
+
+![Teaser](./realism.jpg)
+![Teaser](./editing.jpg)
+![Teaser](./others.jpg)
+
+The FLUX.2 [klein] model family are our fastest image models to date. FLUX.2 [klein] unifies generation and editing in a single compact architecture, **delivering state-of-the-art quality with end-to-end inference in as low as under a second**. Built for applications that require real-time image generation without sacrificing quality, and runs on consumer hardware, with as little as 13GB VRAM.
+
+FLUX.2 [klein] 4B is a 4 billion parameter rectified flow transformer capable of generating images from text descriptions and supports multi-reference editing capabilities.
+
+Fully open under Apache 2.0. Our most accessible model runs on consumer GPUs like the RTX 3090/4070. Compact but capable: supports text-to-image, image editing, and multi-reference at quality that punches above its size. Built for local development, edge deployment, and production use.
+
+For more information, please read our [blog post](https://bfl.ai/blog/flux2-klein-towards-interactive-visual-intelligence).
+
+# **Key Features**
+
+1. Our fastest distilled model for sub-second image generation.
+2. Best suited for interactive workflows, production deployments, and latency-critical applications.
+3. Text-to-image and image-to-image multi-reference editing in a single unified model.
+4. Runs on consumer GPUs (~13GB VRAM).
+5. Open weights available for commercial use under the [Apache 2.0 license](https://www.apache.org/licenses/LICENSE-2.0).
+
+# **Usage**
+
+We provide a reference implementation of FLUX.2 [klein] 4B, as well as sampling code, in a dedicated [GitHub repository](https://github.com/black-forest-labs/flux2). Developers and creatives looking to build on top of FLUX.2 [klein] 4B are encouraged to use this as a starting point.
+
+## **API Endpoints**
+
+The FLUX.2 [klein] 4B model is available via the BFL API:
+
+- [bfl.ai](https://bfl.ai)
+
+FLUX.2 [klein] 4B is also available in both [ComfyUI](https://github.com/comfyanonymous/ComfyUI) and [Diffusers](https://github.com/huggingface/diffusers).
+
+## **Using with Diffusers 🧨**
+
+To use FLUX.2 [klein] 4B with the 🧨 Diffusers python library, first install or upgrade diffusers:
+
+```shell
+pip install git+https://github.com/huggingface/diffusers.git
+```
+Then you can use Flux2KleinPipeline to run the model:
+
+```python
+import torch
+from diffusers import Flux2KleinPipeline
+
+device = "cuda"
+dtype = torch.bfloat16
+
+pipe = Flux2KleinPipeline.from_pretrained("black-forest-labs/FLUX.2-klein-4B", torch_dtype=dtype)
+pipe.enable_model_cpu_offload()  # save some VRAM by offloading the model to CPU
+
+prompt = "A cat holding a sign that says hello world"
+image = pipe(
+    prompt=prompt,
+    height=1024,
+    width=1024,
+    guidance_scale=1.0,
+    num_inference_steps=4,
+    generator=torch.Generator(device=device).manual_seed(0)
+).images[0]
+image.save("flux-klein.png")
+```
+
+
+---
+Limitations
+
+- This model is not intended or able to provide factual information.
+- While the model can output text, text rendered may be inaccurate or subject to distortion.
+- As a statistical model, this checkpoint may represent or amplify biases observed in the training data.
+- The model may fail to generate output that matches the prompts.
+- Prompt following is heavily influenced by the prompting style.
+
+Out-of-Scope Use
+
+The model and its derivatives may not be used:
+
+- In any way that violates applicable law.
+- For the purpose of exploiting, harming or attempting to exploit or harm minors in any way; including but not limited to the solicitation, creation, acquisition, or dissemination of child exploitative content.
+- To generate or disseminate deceptive, fraudulent, misleading or otherwise harmful content.
+- To generate or disseminate personal identifiable information that can be used to harm an individual.
+- To harass, abuse, threaten, stalk, or bully individuals or groups of individuals.
+- To create non-consensual intimate imagery or illegal pornographic content.
+- For fully automated decision making or high risk applications that adversely impact an individual's legal rights or otherwise create or modify a binding, enforceable obligation.
+
+Nothing contained in this Model Card should be interpreted as or deemed a restriction or modification to the license the model is released under.
+
+Hardware
+
+The FLUX.2 [klein] 4B model fits in ~13GB VRAM and is accessible on NVIDIA RTX 3090/4070 and above.
+
+---
+Responsible AI Development
+
+Black Forest Labs is committed to the responsible development and deployment of our models. Prior to releasing the FLUX.2 family of models, we evaluated and mitigated a number of risks in our model checkpoints and hosted services, including the generation of unlawful content, including child sexual abuse material (CSAM) and nonconsensual intimate imagery (NCII). We implemented a series of pre-release mitigations to help prevent misuse by third parties, with additional post-release mitigations to help address residual risks:
+
+1. Pre-training mitigation. We filtered pre-training data for multiple categories of "not safe for work" (NSFW) and known child sexual abuse material (CSAM) to help prevent a user generating unlawful content in response to text prompts or uploaded images. We have partnered with the https://www.iwf.org.uk/, an independent nonprofit organization dedicated to preventing online abuse, to filter known CSAM from the training data.
+2. Post-training mitigation. Subsequently, we undertook multiple rounds of targeted fine-tuning to provide additional mitigation against potential abuse, including both text-to-image (T2I) and image-to-image (I2I) attacks. By inhibiting certain behaviors and suppressing certain concepts in the trained model, these techniques can help to prevent a user generating synthetic CSAM or NCII from a text prompt, or transforming an uploaded image into synthetic CSAM or NCII.
+3. Ongoing evaluation. Throughout this process, we conducted multiple internal and external third-party evaluations of model checkpoints to identify further opportunities for mitigation. External third-party evaluations focused on eliciting CSAM and NCII through adversarial testing with (i) text-only prompts, (ii) a single uploaded reference image with text prompts, and (iii) multiple uploaded reference images with text prompts. Based on this feedback, we conducted further safety fine-tuning to produce our open-weight FLUX.2 [klein] models.
+4. Release decision. After safety fine-tuning and prior to release, we conducted a final third-party evaluation of the proposed release checkpoints, focused on T2I and I2I generation of synthetic CSAM and NCII, including a comparison with other open-weight T2I and I2I models. The final FLUX.2 [klein] checkpoints demonstrated high resilience against violative inputs in complex generation and editing tasks, and demonstrated higher resilience than leading open-weight models across these risk categories. Based on these findings, we approved the release of the open-weight FLUX.2 [klein] 4B models under an Apache 2.0 license and the release of the FLUX.2 [klein] 9B models under a non-commercial license to support third-party research and development.
+5. Inference filters. The repository for the FLUX.2 [klein] models includes filters for NSFW and protected content in inputs and outputs. Filters or manual review must be used with the FLUX.2 [klein] 9B models under the terms of the FLUX Non-Commercial License, and we encourage deployers to implement these mitigations when using the FLUX.2 [klein] 4B models. Where we implement these features on our own hosted services, we may apply multiple filters to intercept text prompts, uploaded images, and output images. We utilize both in-house and third-party filters to mitigate against harmful outputs, such as CSAM and NCII outputs, including filters provided by https://thehive.ai/ and https://www.microsoft.com/.
+6. Content provenance. Content provenance features can help users and platforms better identify, label, and interpret AI-generated content online. The inference code for FLUX.2 [klein] implements an example of pixel-layer watermarking. Additionally, this repository includes links to the https://c2pa.org/ standard for metadata. The API for FLUX.2 [klein] applies cryptographically-signed C2PA metadata to downloaded output content to indicate that images were produced with our model.
+7. Policies. Acceptable use of our models and access to our API are governed by policies set out in applicable documentation, including FLUX Non-Commercial License (for our non-commercial open-weight users); Developer Terms of Service, Self-Hosted Commercial License Terms, and Usage Policy (for our commercial open-weight model users); and Developer Terms of Service, FLUX API Service Terms, and Usage Policy (for our API users). These prohibit the generation of unlawful content or the use of generated content for unlawful, defamatory, or abusive purposes.
+8. Safety. Black Forest Labs takes model safety seriously. We provide a dedicated email address (safety@blackforestlabs.ai) to solicit feedback from the community. We maintain a reporting relationship with organizations such as the https://www.iwf.org.uk/ and the https://www.missingkids.org/, and welcome ongoing engagement with authorities, developers, and researchers to share intelligence about emerging risks and develop effective mitigations.
+
+---
+License
+
+This model is licensed under the https://www.apache.org/licenses/LICENSE-2.0.
+
+Trademarks & IP
+
+This project may contain trademarks or logos for projects, products, or services. Use of Black Forest Labs and FLUX trademarks or logos in modified versions of this project must not cause confusion or imply sponsorship or endorsement. Any use of third-party trademarks, intellectual property or logos are subject to those third-party's policies.

README.md

@@ -1,19 +1,103 @@
 ---
 license: apache-2.0
+license_link: https://www.apache.org/licenses/LICENSE-2.0.txt
+library_name: diffusers
+pipeline_tag: text-to-image
+base_model: black-forest-labs/FLUX.2-klein-4B
+language:
+- en
+tags:
+- text-to-image
+- diffusers
+- flux
+- image-editing
+- optima-tools
 ---
 
-# Optima Tools — image-medium
+# Optima Tools — Génération d'images — Medium
 
-FLUX.2 Klein 4B — pipeline Diffusers : paquet complet pour Optima Tools (génération d’images).
+| | |
+|---|---|
+| Dépôt Hugging Face | `optima-tools-ch/image-medium` |
+| Libellé dans Optima Tools | Génération d'images — Medium |
+| Identifiant du paquet OT | `image.medium` |
+| Modèle | FLUX.2 [klein] 4B — pipeline Diffusers |
+| Source | black-forest-labs/FLUX.2-klein-4B (https://huggingface.co/black-forest-labs/FLUX.2-klein-4B/tree/e7b7dc27f91deacad38e78976d1f2b499d76a294) |
+| Révision source | `e7b7dc27f91deacad38e78976d1f2b499d76a294` |
+| Contenu | 18 fichiers d'exécution, 15,98 Go |
 
-**Copie identique, octet pour octet, de fichiers publiés par leurs auteurs.** Dépôt d'origine : https://huggingface.co/black-forest-labs/FLUX.2-klein-4B (révision `e7b7dc27f91deacad38e78976d1f2b499d76a294`). Aucun fichier n'est modifié.
+## Statut
 
-## Licence
+- **Publié :** les 18 fichiers d'exécution sont présents dans ce dépôt (copie côté serveur Hugging Face le 2026-10-27 ; documents ajoutés le 2026-10-27).
+- **Intégrité :** pour les gros poids, le SHA-256 vient des métadonnées LFS de Hugging Face, identique sur la source et sur ce dépôt ; il n'a **pas été recalculé localement**. Pour les petits fichiers, le SHA-256 a été calculé sur leur contenu, source et destination comparés.
+- **Validation dans Optima Tools : non effectuée.** Cette publication n'est pas un test d'exécution. Les besoins matériels n'ont pas été mesurés et ne sont pas annoncés.
+- Le téléchargement depuis l'application n'est pas encore ouvert.
 
-Apache License 2.0 (Apache-2.0) : https://www.apache.org/licenses/LICENSE-2.0
+## Contenu du paquet
 
-Le texte de licence d'origine est conservé dans ce dépôt : `LICENSE.md`.
+| Dossier | Fichiers | Taille |
+|---|---:|---:|
+| `(racine)` | 1 | 0,0 Mo |
+| `scheduler/` | 1 | 0,0 Mo |
+| `text_encoder/` | 5 | 8,05 Go |
+| `tokenizer/` | 7 | 15,9 Mo |
+| `transformer/` | 2 | 7,75 Go |
+| `vae/` | 2 | 168,1 Mo |
+| **Total** | **18** | **15,98 Go** |
 
-## Vérification
+La liste complète, avec le SHA-256 de chaque fichier, figure dans `SOURCE.json` et `.optima-package.json`.
 
-`.optima-package.json` liste la taille et l'empreinte SHA-256 de chaque fichier ; Optima Tools les vérifie à l'installation.
+**Non repris de la source :** le fichier autonome `flux-2-klein-4b.safetensors` (il dupliquerait le poids du transformeur déjà livré dans `transformer/`) et les images d’illustration `editing.jpg`, `others.jpg` et `realism.jpg`.
+
+## Capacités documentées
+
+- Génération d’images à partir d’un texte (text-to-image).
+- La fiche source documente aussi l’édition d’images et l’édition multi-références dans un même modèle.
+- La fiche source présente un modèle distillé pour une génération rapide (4 étapes dans son exemple).
+- Avec Optima Tools, une image de référence peut être transmise à ce pipeline (Flux2KleinPipeline) pour la retouche ; non validé lors de cette publication.
+
+## Exemple de chargement
+
+Exemple de la fiche source, adapté à un dossier local (`image-medium` contient ce paquet). Le pipeline demande une version récente de Diffusers : le `model_index.json` indique `0.37.0.dev0` et la source recommande l’installation depuis GitHub.
+
+```python
+import torch
+from diffusers import Flux2KleinPipeline
+
+pipe = Flux2KleinPipeline.from_pretrained(
+    "image-medium",  # dossier contenant ce paquet
+    torch_dtype=torch.bfloat16,
+    local_files_only=True,
+)
+pipe.enable_model_cpu_offload()  # économise de la VRAM
+image = pipe(
+    prompt="A cat holding a sign that says hello world",
+    height=1024,
+    width=1024,
+    guidance_scale=1.0,
+    num_inference_steps=4,
+    generator=torch.Generator(device="cuda").manual_seed(0),
+).images[0]
+image.save("flux-klein.png")
+```
+
+Optima Tools charge un dossier de ce type avec `DiffusionPipeline.from_pretrained(dossier, torch_dtype=…, local_files_only=True)`. Cet exemple est adapté de la fiche source et des noms de fichiers livrés ; il n'a pas été exécuté lors de cette publication.
+
+## Licence et crédits
+
+Apache License 2.0 : texte officiel complet dans `LICENSE` ; `LICENSE.md` est la licence fournie par la source, conservée telle quelle. Auteurs, composants, sources, rôle d'Optima Tools (préparateur et distributeur) et modifications : `CREDITS.md` et `CREDITS.json`.
+
+## Documents du dépôt
+
+| Fichier | Contenu |
+|---|---|
+| `README-source.md` | Fiche officielle de la révision source, copie identique |
+| `LICENSE` | Texte officiel complet de la licence Apache 2.0 |
+| `LICENSE.md` | Licence fournie par la source, conservée telle quelle (conditions Apache 2.0 sans annexe ni avis de copyright) |
+| `CREDITS.md`, `CREDITS.json` | Crédits, licences, modifications |
+| `SOURCE.json` | Provenance exacte : chemin source, chemin livré, taille et SHA-256 de chaque fichier |
+| `.optima-package.json` | Manifeste lu par Optima Tools : fichiers d'exécution, licences, crédits et provenance (hors fiche `README.md` et hors lui-même) |
+
+## Droits des auteurs d'origine
+
+Les auteurs d'origine conservent l'ensemble de leurs droits. Optima Tools n'est pas le créateur de ce modèle : ce dépôt en prépare la distribution vérifiée pour l'application, avec mention des sources, des licences et des crédits.

SOURCE.json

@@ -0,0 +1,234 @@
+{
+  "schemaVersion": 1,
+  "preparedAt": "2026-10-27T20:56:07.611Z",
+  "preparedBy": "Optima Tools (optima-tools-ch)",
+  "package": {
+    "id": "image.medium",
+    "repository": "optima-tools-ch/image-medium",
+    "usage": "Génération d'images",
+    "level": "medium",
+    "label": "Génération d'images — Medium",
+    "name": "FLUX.2 [klein] 4B — pipeline Diffusers"
+  },
+  "source": {
+    "host": "huggingface.co",
+    "repository": "black-forest-labs/FLUX.2-klein-4B",
+    "revision": "e7b7dc27f91deacad38e78976d1f2b499d76a294",
+    "url": "https://huggingface.co/black-forest-labs/FLUX.2-klein-4B/tree/e7b7dc27f91deacad38e78976d1f2b499d76a294",
+    "license": "Apache-2.0",
+    "licenseUrl": "https://www.apache.org/licenses/LICENSE-2.0.txt"
+  },
+  "transfer": {
+    "method": "Duplication des fichiers LFS côté serveur Hugging Face (copie par empreinte), puis commit ; petits fichiers téléchargés, vérifiés par SHA-256 et ajoutés au même commit",
+    "downloadedLocally": false,
+    "uploadedFromLocal": false,
+    "modifiedContent": false,
+    "renamedFiles": 0
+  },
+  "verification": {
+    "largeFiles": "SHA-256 = oid LFS lu dans les métadonnées Hugging Face, identique sur la source et la destination ; non recalculé localement",
+    "smallFiles": "SHA-256 calculé sur le contenu téléchargé de la source et de la destination (identiques)",
+    "verifiedAt": "2026-10-27T20:56:07.611Z",
+    "executionTestedInOt": false
+  },
+  "files": [
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+    }
+  ]
+}