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LibreRealESRGANx4t-restore.pt
scaler.pt
ViTOCR Base
This repository contains a pure Transformer-based checkpoint for Khmer OCR. Images are patch-embedded and encoded by a Transformer encoder, then decoded autoregressively.
风格 Style Vetehine Velvet Opium v1.safetensors
Team Gaji Style
Works best at 0.95 weight.
RANDOM_MIX_2D (v1.0)
镭明闪击 Wrap Kinghts Collection - Illustrious (Carlissa)
Flux Sigma Vision Alpha1
Yetigo Style-LyCORIS
Generating character close-ups is better!
Nixmare3D Style - Illustrious
Just a little 3d style from a 3d artist i enjoy :)
VAM_carlotta_X
Another VAM creation. putting 2 versions as the first didn't come out quite right, but I still want to share it
Tron Legacy Style
Trained on SD1.5 using screencaps from the Tron Legacy movie.
CrisSabug - Artist Style [PonyXL]
Trained on AutismMixConfetti Artist gallery:
Mike Mignola Style
use the trigger MignolaStyle at the start, don't describe the style.
Europe Reanalysis Downscaler Convbaseline
The aim of the project is to create a Machine learning (ML) model that can generate high-resolution regional reanalysis data (similar to the one produced by CERRA) by downscaling global reanalysis data from ERA5.
Siglip2 Base Patch16 224 Vision
> Note: This is a stripped-down copy of google/siglip2-base-patch16-224 containing only the vision tower. It encodes images / video frames into the shared embedding space and is meant to be loaded on its own at...
Hair Style: Two face framing tendrils / sidebangs
Hello! This is my first TI, an attempt to teach the diffuser how to generate the [two?] face-framing tendrils hair style.
FireRed Image Edit 1.0
FireRed-Image-Edit is a general-purpose image editing model that delivers high-fidelity and consistent editing across a wide range of scenarios.
Senga Nt Fused Tts
This model is a fine-tuned version of microsoft/speecht5tts on the None dataset. It achieves the following results on the evaluation set: Loss: 0.0868
Flux.1[dev]-pony-PVC-test
The current model is based on flux.1[dev] for clipl model merging. The clipl model using the following model:
