Upload .manifest.json

.manifest.json

@@ -0,0 +1,778 @@
+{
+  "version": 0,
+  "graph": {
+    "nodes": [
+      {
+        "node": {
+          "id": "urn:cid:bafkr4ifpcne3t5pzugtkaqcn5i3nzskjtpfslsnnyejlpte2spfoihzsmi",
+          "properties": {
+            "dataRegistrationJcs": "urn:cid:baga6yaq6edgteubsc6ptupw5ftqbau5sphzghkrxxqvbsdw3plczkd7s3eurq",
+            "nodeType": "data",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "timestamp": "2024-01-29T16:00:24Z"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 108,
+            "asset_name": "NoPattern Roarshac",
+            "owning_project": "NoPattern Rorschach",
+            "asset_description": "The NoPattern Roarshac Model is a generative AI model that allows users to transform images from NoPattern's 'CRASH REPORT' into unique generative creations. This model leverages the artistic content of the 'CRASH REPORT', a 72-page book of experimental 3D imagery, to enable users to find and create their own patterns within NoPattern's art. It embodies the concept of working creatively with imperfect technology and embracing errors and interruptions, as explored in the original 'CRASH REPORT'.",
+            "asset_format": "Generative AI",
+            "asset_type": "Model",
+            "asset_blob_type": "",
+            "source_location_url": "",
+            "contact_info": "https://nopattern.com/Info",
+            "license": "Copyright NoPattern Studio Chicago 2024. All rights reserved.",
+            "license_link": "https://nopattern.com/",
+            "registered_date": "2024-01-29T16:00:32.506622Z",
+            "last_modified_date": "2024-01-29T16:00:32.506622Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4ien22v3j5s6h22rffqenihyzenyh23bln4ir46mbrk3lqjusgbevi",
+          "properties": {
+            "nodeType": "data",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6edtsf5pjack4uz3mwmkr3spgljq2chisbqkf7libfwulrfohxqgby",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "timestamp": "2024-01-29T15:59:03Z"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 107,
+            "asset_name": "laion/CLIP-ViT-H-14-laion2B-s32B-b79K",
+            "owning_project": "LAION-2B",
+            "asset_description": "A CLIP ViT-H/14 model trained using the LAION-2B English subset of LAION-5B, utilizing OpenCLIP. The model, developed by Romain Beaumont on the stability.ai cluster, is designed for zero-shot, arbitrary image classification and aims to aid research in understanding the potential impact of such models.",
+            "asset_format": "OpenCLIP",
+            "asset_type": "Model",
+            "asset_blob_type": "iroh-collection",
+            "source_location_url": "",
+            "contact_info": "Refer to Hugging Face's official channels for contact information.",
+            "license": "MIT",
+            "license_link": "https://doi.org/10.5281/zenodo.5143773",
+            "registered_date": "2024-01-29T16:00:32.444151Z",
+            "last_modified_date": "2024-01-29T16:00:32.444151Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4ifay6uimdc6iv7a5kblryg2zf6nf6nywyuvuut52227xvlcnzzleu",
+          "properties": {
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "nodeType": "data",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6ebn6ucx7ix24yuqoksaurftohczlldwfpqw22rznwufksfr7ovg7i",
+            "timestamp": "2024-01-29T15:59:12Z"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 104,
+            "asset_name": "BLIP: Bootstrapping Language-Image Pre-training",
+            "owning_project": "Salesforce Research",
+            "asset_description": "BLIP is a versatile model capable of performing tasks such as Visual Question Answering, Image-Text Retrieval, and Image Captioning. Developed by Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi, it utilizes Vision-Language Pre-training (VLP) to excel in both understanding-based and generation-based tasks. The model's efficacy is showcased through state-of-the-art results in various vision-language tasks.",
+            "asset_format": "PyTorch",
+            "asset_type": "Model",
+            "asset_blob_type": "iroh-collection",
+            "source_location_url": "",
+            "contact_info": "Refer to the original paper or Salesforce's official channels for contact information.",
+            "license": "bsd-3-clause",
+            "license_link": "https://opensource.org/license/bsd-3-clause/",
+            "registered_date": "2024-01-29T16:00:32.259189Z",
+            "last_modified_date": "2024-01-29T16:00:32.259189Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4iapgxcitooymy4r4ol2ndbnca5l2pvp74ioatyrmkeg2ath4wcozq",
+          "properties": {
+            "timestamp": "2024-01-29T15:59:12Z",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6ebt3lag6yclf3kvthia254sfq6ynfh4vdjpxtbqfayfxynthvo5x6",
+            "nodeType": "data",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 101,
+            "asset_name": "CLIP Interrogator",
+            "owning_project": "CLIP Interrogator",
+            "asset_description": "The CLIP Interrogator is a prompt engineering tool that leverages OpenAI's CLIP and Salesforce's BLIP models. It optimizes text prompts to match images, aiding in the use of text-to-image models like Stable Diffusion for artistic creation. Developed by pharmapsychotic, it's a novel tool for artists and creators.",
+            "asset_format": "Jupyter Notebook",
+            "asset_type": "Code",
+            "asset_blob_type": "",
+            "source_location_url": "",
+            "contact_info": "https://pharmapsychotic.com, Twitter: @pharmapsychotic",
+            "license": "MIT",
+            "license_link": "https://opensource.org/licenses/MIT",
+            "registered_date": "2024-01-29T16:00:32.089085Z",
+            "last_modified_date": "2024-01-29T16:00:32.089085Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4iefsxz5zzn2fx2zpklogxgj3hndx2mbmirxcztz5lyg342jtstk2u",
+          "properties": {
+            "nodeType": "data",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6ecepwli7roalih3iswoppengibpa2qmkj4eg4twqlx7uofat5bods",
+            "timestamp": "2024-01-29T15:58:37Z"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 100,
+            "asset_name": "NoPattern - CRASH REPORT",
+            "owning_project": "NoPattern Rorschach",
+            "asset_description": "CRASH REPORT was a self-published, 72-page book by NoPattern Studio released in November, 2019. Limited to an edition of 300, the book contained a year's worth of experimental, exploratory 3D imagery generated entirely in Photoshop. The concept behind the book deals with our relationship to working creatively with imperfect technology and learning to embrace errors and interruptions.",
+            "asset_format": "Images",
+            "asset_type": "Dataset",
+            "asset_blob_type": "iroh-collection",
+            "source_location_url": "",
+            "contact_info": "https://nopattern.com/Info",
+            "license": "Copyright NoPattern Studio Chicago 2024. All rights reserved.",
+            "license_link": "https://nopattern.com/",
+            "registered_date": "2024-01-29T16:00:31.997347Z",
+            "last_modified_date": "2024-01-29T16:00:31.997348Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4ieqv4gkv6vvpb3twx2qdrg3p76evukyhgbtc6zyqo4cmktx6fj56q",
+          "properties": {
+            "timestamp": "2024-01-29T15:58:37Z",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6eajymqff5koge2wpehyoh45i6kzkl4ix6yrpz4yloxvhpd6omc3rm",
+            "nodeType": "data"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 96,
+            "asset_name": "normalize.py",
+            "owning_project": "NoPattern Rorschach",
+            "asset_description": "Converts NoPattern Images to 1024x1024 white background images",
+            "asset_format": "python",
+            "asset_type": "Code",
+            "asset_blob_type": "",
+            "source_location_url": "",
+            "contact_info": "https://nopattern.com/Info",
+            "license": "Copyright NoPattern Studio Chicago 2024. All rights reserved.",
+            "license_link": "https://nopattern.com/",
+            "registered_date": "2024-01-29T16:00:31.737289Z",
+            "last_modified_date": "2024-01-29T16:00:31.73729Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "properties": {
+            "operatedBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "vcRegistrationsJcs": [
+              "urn:cid:baga6yaq6ebnt3hgw3nmnnmprnfakxwqiaxfilhhkc3n7dd2mrbxi6kf7kawbw"
+            ],
+            "nodeType": "computation",
+            "timestamp": "2024-01-29T15:58:37Z",
+            "jcsCID": "urn:cid:baga6yaq6eaepmsdyqrnqmz3lz5dyrdxro3mqrntnnwiiyxweqgm2aekfpzwlm"
+          }
+        },
+        "enrichments": {}
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4iafqm6lpxq3dvy4slq7lmfy5zxvsoso2gm3nvbqbgam6xyc4lmr4m",
+          "properties": {
+            "timestamp": "2024-01-29T15:58:37Z",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "nodeType": "data",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6ec4whnu5avsfe4hyq2t5ap6v65llq6zydvomcsiypbg6euxx6kidi"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 106,
+            "asset_name": "Normalized NoPattern CRASH REPORT Imagery",
+            "owning_project": "NoPattern Rorschach",
+            "asset_description": "1024x1024 white background images of - CRASH REPORT was a self-published, 72-page book by NoPattern Studio released in November, 2019. Limited to an edition of 300, the book contained a year's worth of experimental, exploratory 3D imagery generated entirely in Photoshop. The concept behind the book deals with our relationship to working creatively with imperfect technology and learning to embrace errors and interruptions.",
+            "asset_format": "Images",
+            "asset_type": "Dataset",
+            "asset_blob_type": "iroh-collection",
+            "source_location_url": "",
+            "contact_info": "https://nopattern.com/Info",
+            "license": "Copyright NoPattern Studio Chicago 2024. All rights reserved.",
+            "license_link": "https://nopattern.com/",
+            "registered_date": "2024-01-29T16:00:32.381507Z",
+            "last_modified_date": "2024-01-29T16:00:32.381507Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bagb6qaq6ede2ppixa73ox3etfkjr4o23kv6yczab4xmuxwe4hr75vokuz76nq",
+          "properties": {
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "jcsCID": "urn:cid:baga6yaq6edlbrkeexnnhmuvijdai2ydhmc7it7jlkvsrluhzqhti3gdyjbtig",
+            "timestamp": "2024-01-29T15:59:12Z",
+            "vcRegistrationsJcs": [
+              "urn:cid:baga6yaq6eauf5h3zyu7k5bc5toy47ou5uoxvlwlzcsewywdnohmsoig6opiou"
+            ],
+            "nodeType": "computation",
+            "operatedBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY"
+          }
+        },
+        "enrichments": {}
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4ieudbqko5jn3kkwhtkcje4nflw2bzitm26lurm2bphgddtulqvivu",
+          "properties": {
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6ecbq3r37leu53ooxxiq2yq7qkxuhxten6vim4232h57kzrz5vugk2",
+            "nodeType": "data",
+            "timestamp": "2024-01-29T15:59:12Z"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 109,
+            "asset_name": "AI-Captioned Dataset",
+            "owning_project": "No Pattern - CRASH REPORT",
+            "asset_description": "This dataset, named 'desc.csv', consists of AI-generated captions for images from the 'No Pattern - CRASH REPORT'. The captions were generated using the CLIP Interrogator, a tool that employs OpenAI's CLIP and Salesforce's BLIP models to optimize text prompts for images. The dataset offers unique insights into AI's interpretation of visual content.",
+            "asset_format": "CSV",
+            "asset_type": "Dataset",
+            "asset_blob_type": "",
+            "source_location_url": "",
+            "contact_info": "",
+            "license": "Dependent on the licensing of the source images and the CLIP Interrogator tool",
+            "license_link": "Non-commercial",
+            "registered_date": "2024-01-29T16:00:32.562955Z",
+            "last_modified_date": "2024-01-29T16:00:32.562955Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4iauvrrmfbm4oiiqex4e7qazphp4sxe67brr7dld2rhwqkfutkd6va",
+          "properties": {
+            "dataRegistrationJcs": "urn:cid:baga6yaq6eb5z53fkpc3mcrwfn6rnhpky7cfupzavbykfbon5djjwtopyz6b2c",
+            "nodeType": "data",
+            "timestamp": "2024-01-29T15:59:12Z",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 97,
+            "asset_name": "convert to json py",
+            "owning_project": "Rorschach",
+            "asset_description": "A Python script named 'convert_to_json.py' that converts the 'desc.csv' file to json lines, containing AI-generated captions for images, into a JSON format. This script facilitates the easy integration and processing of the captioned data in various applications that require JSON format.",
+            "asset_format": "Python",
+            "asset_type": "Code",
+            "asset_blob_type": "",
+            "source_location_url": "",
+            "contact_info": "backnotprop",
+            "license": "no license",
+            "license_link": "no license link",
+            "registered_date": "2024-01-29T16:00:31.797419Z",
+            "last_modified_date": "2024-01-29T16:00:31.797419Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bagb6qaq6echai7ljrudfr7jdf7p5xwdxkb4xofhwjjjstcc7f6dzybz5hy3d4",
+          "properties": {
+            "timestamp": "2024-01-29T15:59:12Z",
+            "vcRegistrationsJcs": [
+              "urn:cid:baga6yaq6ea4pydrkxuufdpaswb2xnbg6medybree2pgr6od734s73mmmgvpj2"
+            ],
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "operatedBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "jcsCID": "urn:cid:baga6yaq6eaywa6buvdncfajqgh5pqvwe6mni5ajko5qyy72imfkik6jmzyj4e",
+            "nodeType": "computation"
+          }
+        },
+        "enrichments": {}
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4ifxrye76qsvscdwy4odbqxszodph7xkhmtk3bvfb2aywwfkrchf4i",
+          "properties": {
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6ea4f3ggulis6er5ip44bfpo2jlprkm4jcw272bgem2pz7fvxxdeua",
+            "timestamp": "2024-01-29T15:59:12Z",
+            "nodeType": "data"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 105,
+            "asset_name": "metadata.jsonl",
+            "owning_project": "AI-Captioned Dataset Conversion",
+            "asset_description": "The 'metadata.jsonl' file is the output of the 'convert_to_json.py' script. It contains AI-generated captions from the 'desc.csv' file, now formatted in newline JSON (JSONL). Each line of the file is a separate JSON object, making it suitable for streamlined processing in various data analysis and machine learning applications.",
+            "asset_format": "JSONL (Newline JSON)",
+            "asset_type": "Dataset",
+            "asset_blob_type": "",
+            "source_location_url": "",
+            "contact_info": "",
+            "license": "Non - commercial",
+            "license_link": "",
+            "registered_date": "2024-01-29T16:00:32.315359Z",
+            "last_modified_date": "2024-01-29T16:00:32.315359Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4iefsxz5zzn2fx2zpklogxgj3hndx2mbmirxcztz5lyg342jtstk2u",
+          "properties": {
+            "nodeType": "data",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6ecepwli7roalih3iswoppengibpa2qmkj4eg4twqlx7uofat5bods",
+            "timestamp": "2024-01-29T15:58:37Z"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 100,
+            "asset_name": "NoPattern - CRASH REPORT",
+            "owning_project": "NoPattern Rorschach",
+            "asset_description": "CRASH REPORT was a self-published, 72-page book by NoPattern Studio released in November, 2019. Limited to an edition of 300, the book contained a year's worth of experimental, exploratory 3D imagery generated entirely in Photoshop. The concept behind the book deals with our relationship to working creatively with imperfect technology and learning to embrace errors and interruptions.",
+            "asset_format": "Images",
+            "asset_type": "Dataset",
+            "asset_blob_type": "iroh-collection",
+            "source_location_url": "",
+            "contact_info": "https://nopattern.com/Info",
+            "license": "Copyright NoPattern Studio Chicago 2024. All rights reserved.",
+            "license_link": "https://nopattern.com/",
+            "registered_date": "2024-01-29T16:00:31.997347Z",
+            "last_modified_date": "2024-01-29T16:00:31.997348Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4ieqv4gkv6vvpb3twx2qdrg3p76evukyhgbtc6zyqo4cmktx6fj56q",
+          "properties": {
+            "timestamp": "2024-01-29T15:58:37Z",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6eajymqff5koge2wpehyoh45i6kzkl4ix6yrpz4yloxvhpd6omc3rm",
+            "nodeType": "data"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 96,
+            "asset_name": "normalize.py",
+            "owning_project": "NoPattern Rorschach",
+            "asset_description": "Converts NoPattern Images to 1024x1024 white background images",
+            "asset_format": "python",
+            "asset_type": "Code",
+            "asset_blob_type": "",
+            "source_location_url": "",
+            "contact_info": "https://nopattern.com/Info",
+            "license": "Copyright NoPattern Studio Chicago 2024. All rights reserved.",
+            "license_link": "https://nopattern.com/",
+            "registered_date": "2024-01-29T16:00:31.737289Z",
+            "last_modified_date": "2024-01-29T16:00:31.73729Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "properties": {
+            "operatedBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "vcRegistrationsJcs": [
+              "urn:cid:baga6yaq6ebnt3hgw3nmnnmprnfakxwqiaxfilhhkc3n7dd2mrbxi6kf7kawbw"
+            ],
+            "nodeType": "computation",
+            "timestamp": "2024-01-29T15:58:37Z",
+            "jcsCID": "urn:cid:baga6yaq6eaepmsdyqrnqmz3lz5dyrdxro3mqrntnnwiiyxweqgm2aekfpzwlm"
+          }
+        },
+        "enrichments": {}
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4iafqm6lpxq3dvy4slq7lmfy5zxvsoso2gm3nvbqbgam6xyc4lmr4m",
+          "properties": {
+            "timestamp": "2024-01-29T15:58:37Z",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "nodeType": "data",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6ec4whnu5avsfe4hyq2t5ap6v65llq6zydvomcsiypbg6euxx6kidi"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 106,
+            "asset_name": "Normalized NoPattern CRASH REPORT Imagery",
+            "owning_project": "NoPattern Rorschach",
+            "asset_description": "1024x1024 white background images of - CRASH REPORT was a self-published, 72-page book by NoPattern Studio released in November, 2019. Limited to an edition of 300, the book contained a year's worth of experimental, exploratory 3D imagery generated entirely in Photoshop. The concept behind the book deals with our relationship to working creatively with imperfect technology and learning to embrace errors and interruptions.",
+            "asset_format": "Images",
+            "asset_type": "Dataset",
+            "asset_blob_type": "iroh-collection",
+            "source_location_url": "",
+            "contact_info": "https://nopattern.com/Info",
+            "license": "Copyright NoPattern Studio Chicago 2024. All rights reserved.",
+            "license_link": "https://nopattern.com/",
+            "registered_date": "2024-01-29T16:00:32.381507Z",
+            "last_modified_date": "2024-01-29T16:00:32.381507Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4ihh57vo2fq2imhen3ak6i6pksohtlqwhoctcvjrqhbypzunmbv6j4",
+          "properties": {
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6eakw4oxifelrw4kvr4o6tjdwytie4hgzp5pozzdk76ozoz6f22dwg",
+            "timestamp": "2024-01-29T16:00:22Z",
+            "nodeType": "data"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 102,
+            "asset_name": "SDXL-Turbo",
+            "owning_project": "Stability AI",
+            "asset_description": "SDXL-Turbo is a distilled version of SDXL 1.0, trained for real-time synthesis. It uses Adversarial Diffusion Distillation (ADD) for sampling large-scale foundational image diffusion models in 1 to 4 steps with high image quality. This approach combines score distillation with an adversarial loss, leveraging large-scale image diffusion models as a teacher signal to ensure high fidelity in low-step sampling.",
+            "asset_format": "PyTorch",
+            "asset_type": "Model",
+            "asset_blob_type": "iroh-collection",
+            "source_location_url": "",
+            "contact_info": "Refer to the official Stability AI channels or the technical report for contact information.",
+            "license": "sai-nc-community",
+            "license_link": "https://huggingface.co/stabilityai/sdxl-turbo/blob/main/LICENSE.TXT",
+            "registered_date": "2024-01-29T16:00:32.147672Z",
+            "last_modified_date": "2024-01-29T16:00:32.147672Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4ihjtsf3mnk5knzcv5rsql5flz2qm4x2kj7tqw2t3ukgtwyy7kixny",
+          "properties": {
+            "dataRegistrationJcs": "urn:cid:baga6yaq6eacodu4hepmrm2sogq3kirqr47xi6prup32tytlhkabvsxffqls3s",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "timestamp": "2024-01-29T16:00:23Z",
+            "nodeType": "data"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 98,
+            "asset_name": "style-transfer-pytorch",
+            "owning_project": "",
+            "asset_description": "An implementation of neural style transfer in PyTorch, supporting CPUs and Nvidia GPUs. It offers automatic multi-scale stylization for high-quality high-resolution outputs, compatible even up to print resolution. The code supports dual GPU usage for higher maximum resolution. Modifications from the original algorithm include the use of PyTorch pre-trained VGG-19 weights, 'replicate' padding mode in the first layer of VGG-19, scaled results for average/L2 pooling, Wasserstein-2 style loss, an exponential moving average over iterates, warm-starting of the Adam optimizer, non-equal weights for style layers, and progressive scaling of image stylization.",
+            "asset_format": "PyTorch",
+            "asset_type": "Code",
+            "asset_blob_type": "iroh-collection",
+            "source_location_url": "",
+            "contact_info": "https://twitter.com/RiversHaveWings",
+            "license": "MIT",
+            "license_link": "https://github.com/crowsonkb/style-transfer-pytorch/blob/master/LICENSE",
+            "registered_date": "2024-01-29T16:00:31.86777Z",
+            "last_modified_date": "2024-01-29T16:00:31.86777Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4ibolvbapfc6uckeqb3nlxw3zbecufb7m2i65mgfkbp35elxmqhsdy",
+          "properties": {
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "timestamp": "2024-01-29T16:00:23Z",
+            "dataRegistrationJcs": "urn:cid:baga6yaq6easfw34bfqzruffkg3cfcv5zelaeoq7eqlnguaefgyqn7b5y2xs6a",
+            "nodeType": "data"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 99,
+            "asset_name": "unofficial-SDXL-Turbo-i2i-t2i",
+            "owning_project": "NoPattern Project",
+            "asset_description": "An application for image-to-image (i2i) and text-to-image (t2i) generation using the SDXL-Turbo model. It was developed for the 'No Pattern' project, showcasing the model's capability in image synthesis based on textual and visual inputs.",
+            "asset_format": "Python",
+            "asset_type": "Code",
+            "asset_blob_type": "iroh-collection",
+            "source_location_url": "",
+            "contact_info": "https://twitter.com/radamar",
+            "license": "refer to developer",
+            "license_link": "https://twitter.com/radamar",
+            "registered_date": "2024-01-29T16:00:31.92389Z",
+            "last_modified_date": "2024-01-29T16:00:31.92389Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bafkr4ieew2ui4vcemfibfbv4csgykzf7bz3pk3gmx3zdahupph7tv26jfm",
+          "properties": {
+            "dataRegistrationJcs": "urn:cid:baga6yaq6eck5l2xjlngsomwfos67jz2ohieh344zqru3xvunibf2trxiuqyea",
+            "timestamp": "2024-01-29T16:00:24Z",
+            "nodeType": "data",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY"
+          }
+        },
+        "enrichments": {
+          "asset_hub": {
+            "asset_id": 103,
+            "asset_name": "VGG-19",
+            "owning_project": "ImageNet Challenge 2014",
+            "asset_description": "VGG-19 is a convolutional neural network that is 19 layers deep. It was developed by Karen Simonyan and Andrew Zisserman. The model is notable for its depth and the use of very small (3x3) convolution filters. VGG-19 achieved significant improvements in accuracy in large-scale image recognition by increasing network depth. It was part of the ImageNet Challenge 2014 submission, where it performed exceptionally well in the localisation and classification tracks. The pretrained network is capable of classifying images into 1000 categories and is widely used for various computer vision tasks.",
+            "asset_format": "PyTorch",
+            "asset_type": "Model",
+            "asset_blob_type": "",
+            "source_location_url": "",
+            "contact_info": "Refer to the original paper or the PyTorch official channels for contact information.",
+            "license": "Refer to the PyTorch repository for licensing information.",
+            "license_link": "",
+            "registered_date": "2024-01-29T16:00:32.203438Z",
+            "last_modified_date": "2024-01-29T16:00:32.203438Z"
+          }
+        }
+      },
+      {
+        "node": {
+          "id": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "properties": {
+            "timestamp": "2024-01-29T16:00:24Z",
+            "operatedBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "registeredBy": "did:key:z6MkhQD1A9eMQ8bZNGmBiCVz7kG4mfnApD7WjHKNhkZp7HEY",
+            "nodeType": "computation",
+            "vcRegistrationsJcs": [
+              "urn:cid:baga6yaq6eatc33h6gj4rzaisnns2mz5deqvjze2abqgbampr2plj34bi4tn52"
+            ],
+            "jcsCID": "urn:cid:baga6yaq6ecv3jxizi6mequnttcp6mxetice7gtperf5xkh7syjcqvg37id5x4"
+          }
+        },
+        "enrichments": {}
+      }
+    ],
+    "edges": [
+      {
+        "edge": {
+          "id": "024d9b65-fcd0-42fe-b94c-ab84ddd067d1",
+          "source_id": "urn:cid:bafkr4iefsxz5zzn2fx2zpklogxgj3hndx2mbmirxcztz5lyg342jtstk2u",
+          "target_id": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "statement": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "769578a3-d99c-43ce-812f-8aed6a4cd9e7",
+          "source_id": "urn:cid:bafkr4ieqv4gkv6vvpb3twx2qdrg3p76evukyhgbtc6zyqo4cmktx6fj56q",
+          "target_id": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "statement": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "3134cd82-9bd5-4e11-9fb1-69fd0ca6abe9",
+          "source_id": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "target_id": "urn:cid:bafkr4iafqm6lpxq3dvy4slq7lmfy5zxvsoso2gm3nvbqbgam6xyc4lmr4m",
+          "statement": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "label": "output"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "ca6c7b16-d442-4976-954c-bd78a72ca400",
+          "source_id": "urn:cid:bafkr4ien22v3j5s6h22rffqenihyzenyh23bln4ir46mbrk3lqjusgbevi",
+          "target_id": "urn:cid:bagb6qaq6ede2ppixa73ox3etfkjr4o23kv6yczab4xmuxwe4hr75vokuz76nq",
+          "statement": "urn:cid:bagb6qaq6ede2ppixa73ox3etfkjr4o23kv6yczab4xmuxwe4hr75vokuz76nq",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "48ce193a-95de-46e9-b971-2d8468e7bb7a",
+          "source_id": "urn:cid:bafkr4ifay6uimdc6iv7a5kblryg2zf6nf6nywyuvuut52227xvlcnzzleu",
+          "target_id": "urn:cid:bagb6qaq6ede2ppixa73ox3etfkjr4o23kv6yczab4xmuxwe4hr75vokuz76nq",
+          "statement": "urn:cid:bagb6qaq6ede2ppixa73ox3etfkjr4o23kv6yczab4xmuxwe4hr75vokuz76nq",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "8da6d8de-ef03-4323-b68e-831ac3f96460",
+          "source_id": "urn:cid:bafkr4iapgxcitooymy4r4ol2ndbnca5l2pvp74ioatyrmkeg2ath4wcozq",
+          "target_id": "urn:cid:bagb6qaq6ede2ppixa73ox3etfkjr4o23kv6yczab4xmuxwe4hr75vokuz76nq",
+          "statement": "urn:cid:bagb6qaq6ede2ppixa73ox3etfkjr4o23kv6yczab4xmuxwe4hr75vokuz76nq",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "d2fd94bf-3738-4c0e-89d0-6e5080c67c91",
+          "source_id": "urn:cid:bafkr4iafqm6lpxq3dvy4slq7lmfy5zxvsoso2gm3nvbqbgam6xyc4lmr4m",
+          "target_id": "urn:cid:bagb6qaq6ede2ppixa73ox3etfkjr4o23kv6yczab4xmuxwe4hr75vokuz76nq",
+          "statement": "urn:cid:bagb6qaq6ede2ppixa73ox3etfkjr4o23kv6yczab4xmuxwe4hr75vokuz76nq",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "56c675f4-c337-43f9-bc56-faf926f740ba",
+          "source_id": "urn:cid:bagb6qaq6ede2ppixa73ox3etfkjr4o23kv6yczab4xmuxwe4hr75vokuz76nq",
+          "target_id": "urn:cid:bafkr4ieudbqko5jn3kkwhtkcje4nflw2bzitm26lurm2bphgddtulqvivu",
+          "statement": "urn:cid:bagb6qaq6ede2ppixa73ox3etfkjr4o23kv6yczab4xmuxwe4hr75vokuz76nq",
+          "label": "output"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "32aea65b-5a16-4b76-a974-809a09859077",
+          "source_id": "urn:cid:bafkr4ieudbqko5jn3kkwhtkcje4nflw2bzitm26lurm2bphgddtulqvivu",
+          "target_id": "urn:cid:bagb6qaq6echai7ljrudfr7jdf7p5xwdxkb4xofhwjjjstcc7f6dzybz5hy3d4",
+          "statement": "urn:cid:bagb6qaq6echai7ljrudfr7jdf7p5xwdxkb4xofhwjjjstcc7f6dzybz5hy3d4",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "29c59065-bb6e-4d50-ab09-78cff27d4c07",
+          "source_id": "urn:cid:bafkr4iauvrrmfbm4oiiqex4e7qazphp4sxe67brr7dld2rhwqkfutkd6va",
+          "target_id": "urn:cid:bagb6qaq6echai7ljrudfr7jdf7p5xwdxkb4xofhwjjjstcc7f6dzybz5hy3d4",
+          "statement": "urn:cid:bagb6qaq6echai7ljrudfr7jdf7p5xwdxkb4xofhwjjjstcc7f6dzybz5hy3d4",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "a633e1d9-9b94-4c7e-91b2-a78e5a610bb7",
+          "source_id": "urn:cid:bagb6qaq6echai7ljrudfr7jdf7p5xwdxkb4xofhwjjjstcc7f6dzybz5hy3d4",
+          "target_id": "urn:cid:bafkr4ifxrye76qsvscdwy4odbqxszodph7xkhmtk3bvfb2aywwfkrchf4i",
+          "statement": "urn:cid:bagb6qaq6echai7ljrudfr7jdf7p5xwdxkb4xofhwjjjstcc7f6dzybz5hy3d4",
+          "label": "output"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "024d9b65-fcd0-42fe-b94c-ab84ddd067d1",
+          "source_id": "urn:cid:bafkr4iefsxz5zzn2fx2zpklogxgj3hndx2mbmirxcztz5lyg342jtstk2u",
+          "target_id": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "statement": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "769578a3-d99c-43ce-812f-8aed6a4cd9e7",
+          "source_id": "urn:cid:bafkr4ieqv4gkv6vvpb3twx2qdrg3p76evukyhgbtc6zyqo4cmktx6fj56q",
+          "target_id": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "statement": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "3134cd82-9bd5-4e11-9fb1-69fd0ca6abe9",
+          "source_id": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "target_id": "urn:cid:bafkr4iafqm6lpxq3dvy4slq7lmfy5zxvsoso2gm3nvbqbgam6xyc4lmr4m",
+          "statement": "urn:cid:bagb6qaq6edb3w3oq2ldhgtupd4n7ye2lg3jzr33rimpccuclcawxdevub5bqi",
+          "label": "output"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "ccc32512-f1e6-43ee-b5ed-b6ab36375d73",
+          "source_id": "urn:cid:bafkr4ifxrye76qsvscdwy4odbqxszodph7xkhmtk3bvfb2aywwfkrchf4i",
+          "target_id": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "statement": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "0f52e75a-18e9-4fdc-9ae2-7d087ecf5e64",
+          "source_id": "urn:cid:bafkr4iafqm6lpxq3dvy4slq7lmfy5zxvsoso2gm3nvbqbgam6xyc4lmr4m",
+          "target_id": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "statement": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "e3c5fa25-1f7b-474c-a540-155edb7d1a43",
+          "source_id": "urn:cid:bafkr4ihh57vo2fq2imhen3ak6i6pksohtlqwhoctcvjrqhbypzunmbv6j4",
+          "target_id": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "statement": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "bd5f9f0e-6739-4cb0-8805-57cb1e17a9c4",
+          "source_id": "urn:cid:bafkr4ihjtsf3mnk5knzcv5rsql5flz2qm4x2kj7tqw2t3ukgtwyy7kixny",
+          "target_id": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "statement": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "7ab3061e-06bc-433e-8454-964bef6bba58",
+          "source_id": "urn:cid:bafkr4ibolvbapfc6uckeqb3nlxw3zbecufb7m2i65mgfkbp35elxmqhsdy",
+          "target_id": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "statement": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "a5726459-30f9-4dcc-a4b0-19f71ea1e1c3",
+          "source_id": "urn:cid:bafkr4ieew2ui4vcemfibfbv4csgykzf7bz3pk3gmx3zdahupph7tv26jfm",
+          "target_id": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "statement": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "label": "input"
+        },
+        "enrichments": {}
+      },
+      {
+        "edge": {
+          "id": "426e4811-b281-4af5-9cf1-179886e03110",
+          "source_id": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "target_id": "urn:cid:bafkr4ifpcne3t5pzugtkaqcn5i3nzskjtpfslsnnyejlpte2spfoihzsmi",
+          "statement": "urn:cid:bagb6qaq6ecap337kroqsu5twfdwoqjhwe73pb7qra6d5t22h5tsj2sxtdlzka",
+          "label": "output"
+        },
+        "enrichments": {}
+      }
+    ]
+  },
+  "governance": {},
+  "text": {},
+  "iroh-collection": {}
+}