ModelPrésentéExterne

2xLexicaRRDBNet

Sourcehuggingface.co/Phips/2xLexicaRRDBNet/tree/bfdfcfd657cab0cd83b10279a658aad57cd1ed30

TypeOtherVersion2x Lexica RRDBNetCClasse

Source du modèle

Type: Other
Taille du fichier: 31,9 MB
Version: v2x Lexica RRDBNet
Mis à jour: 27 oct. 2026
Source: Hugging Face

Description de la source

Link to Github Release

2xLexicaRRDBNet

Name: 2xLexicaRRDBNet
Author: Philip Hofmann
Release Date: 01.06.2023
License: CC BY 4.0
Network: RRDBNet
Scale: 2
Purpose: Upscaling AI generated images
Iterations: 185'000
batch_size: 4
HR_size: 128
Epoch: 17 (require iter number per epoch: 10964)
Dataset: lexica-aperture-v3-small
Number of train images: 43856
OTF Training: No
Pretrained_Model_G: None

Description: 2x upscaler for the AI generated image output. Trained on 43856 images from lexica.art, so its trained specifically on that model but should work in general on ai generated images.

16 Examples with Input, Upscaled (Normal and Sharp) and GT Files, plus example data: https://drive.google.com/drive/folders/1LT20d5u1m8CryCrXOJ7pWJd0mlN7X5yA

Example1 Example2 Example3 Example4 Example5 Example6 Example7 Example8 Example9 Example10 Example11 Example12 Example13 Example14 Example15 Example16

Sources

1 source

Hugging FacePrincipalVersion bfdfcfd657cab0cd83b10279a658aad57cd1ed30

huggingface.co/Phips/2xLexicaRRDBNet/tree/bfdfcfd657cab0cd83b10279a658aad57cd1ed30

Vérifié 26 oct.

Artefacts du modèle

1 artefact

2xLexicaRRDBNet.safetensors

safetensors · 31,9 MB · SHA-256 bfde020eaca9…3d69 · Hugging Face

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Extraits de sources

2 extraits

Readme8 aoûthuggingface.co/Phips/2xLexicaRRDBNet

--- license: cc-by-4.0 pipeline_tag: image-to-image tags: - pytorch - super-resolution --- [Link to Github Release](https://github.com/Phhofm/models/releases/tag/2xLexicaRRDBNet) # 2xLexicaRRDBNet Name: 2xLexicaRRDBNet Author: Philip Hofmann Release Date: 01.06.2023 License: CC BY 4.0 Network: RRDBNet Scale: 2 Purpose: Upscaling AI generated images Iterations: 185'000 batch_size: 4 HR_size: 128 Epoch: 17 (require iter number per epoch: 10964) Dataset: lexica-aperture-v3-small Number of train images: 43856 OTF Training: No Pretrained_Model_G: None Description: 2x upscaler for the AI generated image output. Trained on 43856 images from lexica.art, so its trained specifically on that model but should work in general on ai generated images. 16 Examples with Input, Upscaled (Normal and Sharp) and GT Files, plus example data: https://drive.google.com/drive/folders/1LT20d5u1m8CryCrXOJ7pWJd0mlN7X5yA ![Example1](https://github.com/Phhofm/models/assets/14755670/3812501e-ef5a-4d8d-b286-3ac73c1c14ec) ![Example2](https://github.com/Phhofm/models/assets/14755670/c69c7b9a-b31f-4246-8133-d6559f1ab378) ![Example3](https://github.com/Phhofm/models/assets/14755670/5eaafd0d-8829-4cd0-8bc1-0973306f5b95) ![Example4](https://github.com/Phhofm/models/assets/14755670/b128687b-35e5-4505-9a7c-1430de309bf0) ![Example5](https://github.com/Phhofm/models/assets/14755670/47109b66-3a24-47c8-be16-ffd294126d06) ![Example6](https://github.com/Phhofm/models/assets/14755670/d533bb3b-20a4-4b72-8c2a-e3e5dbfbc138) ![Example7](https://github.com/Phhofm/models/assets/14755670/7e9d9384-297b-4b30-9638-91235a1b8a14) ![Example8](https://github.com/Phhofm/models/assets/14755670/58228d65-6222-49ec-8672-59a81110d600) ![Example9](https://github.com/Phhofm/models/assets/14755670/2c18374e-b8e6-4807-a1c7-38db257de189) ![Example10](https://github.com/Phhofm/models/assets/14755670/e7d1be71-404f-4982-babc-c6028d2f54b8) ![Example11](https://github.com/Phhofm/models/assets/14755670/1451bd2f-164c-4e50-83ed-6c06711f82f8) ![Example12](https://github.com/Phhofm/models/assets/14755670/9b49469a-8a5a-4d8d-abd7-92ff3c5e132e) ![Example13](https://github.com/Phhofm/models/assets/14755670/a3651ddb-58be-427a-ad62-5f4523e3eebb) ![Example14](https://github.com/Phhofm/models/assets/14755670/5639e063-1b22-46a8-a2f0-dd502e5285f0) ![Example15](https://github.com/Phhofm/models/assets/14755670/5eabc77c-ec3a-4e0b-9422-6472fb229...

Note8 aoûthuggingface.co/Phips/2xLexicaRRDBNet

Source context: 0 downloads · 0 likes · Pipeline image-to-image · Repo Phips/2xLexicaRRDBNet