Resource directory
Find what you need for your workflow.
Guides: techniques, setup, and troubleshootingSearch Sweet Tea Pipes, external workflows, models, node packs, and guides in one evidence-linked catalog.
Start with a workflow instead ↗Search results
All resources
20 shown of 41,760
【SDXL】INPAINT — v4.0
🔄 Full Nodes 2.0 rewrite
SD ControlNet Mediapipe
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below. prompt: Maayan Gazuli performing sign language in front of a green screen....
Qwen3 4b Ticket Translation LoRA
Developed by: [More Information Needed] Funded by [optional]: [More Information Needed] Shared by [optional]: [More Information Needed] Model type: [More Information Needed] Language(s) (NLP): [More Information...
Anime Scoring Model Test
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
Wav2Vec2 Small AntiDeepfake
Bit-exact copy of nii-yamagishilab/wav2vec-small-anti-deepfake (the AntiDeepfake collection, nii-yamagishilab), hosted for the Speech Anti-Spoofing Arena. Trained with RawBoost data augmentation (default).
LongCat Image DF11
For more information (including how to compress models yourself), check out and
Marlin Vit Small Ytf
This repo is the official PyTorch implementation for the paper MARLIN: Masked Autoencoder for facial video Representation LearnINg (CVPR 2023) (arXiv).
LLaMA Mesh Q4 Mlx
The Model alexgusevski/LLaMA-Mesh-q4-mlx was converted to MLX format from Zhengyi/LLaMA-Mesh using mlx-lm version 0.21.4.
Cocktail Fork MRX Adapted Loudness
Apple MLX port of MERL's MRX (Multi-Resolution CrossNet) — separates a soundtrack mixture into music, speech, and sound effects (sfx).
Voiceclonnx Knn Vc
ONNX export of kNN-VC (Baas et al., Interspeech 2023, MIT) for the vconnx voice-conversion library: WavLM-Large layer-6 feature extractor + prematched HiFi-GAN vocoder; the kNN regression step is pure numpy at...
Wan 2.2 5B TheDenk Depth ControlNet NonAR DMD 4Step LoRA R64 Iter3000
This repository contains the generator-only Wan transformer LoRA trained by 4-step DMD while a frozen TheDenk/wan2.2-ti2v-5b-controlnet-depth-v1 provided dynamic depth conditioning to the student, teacher, and critic.
Distilhubert Finetuned Gtzan
This model is a fine-tuned version of ntu-spml/distilhubert on the GTZAN dataset. It achieves the following results on the evaluation set: Loss: 0.7235 Accuracy: 0.87
Siglip2 So400m Patch16 512 Ces 32768
This model is a 22.63% smaller version of google/siglip2-so400m-patch16-512 optimized for Czech language via vocabulary size reduction using the trimming method. This trimmed model should perform similarly to the...
Shi Ci Vision
Chinese, English Test 0 of all. Released as an early preview of our v3.1 LLMs. The v3.1 series covers the "Shi-Ci", "AnFeng" and "Trigonotis" LLM products. The sizes are labelled from small to large "Nano" "Leap"...
Frisky Dingo🐕 (N/SFW, IL-XL Hybrid)
👍 Please Rate! - Your feedback, rating or a follow are greatly appreciated. - Thankyou! 😊
Andina Dinov3 Vits Triplet
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
Sd15.controlnet.sam
@misc{zhang2023adding, title = {Adding Conditional Control to Text-to-Image Diffusion Models}, author = {Lvmin Zhang and Maneesh Agrawala}, year = 2023, url = { eprint = {2302.05543}, archiveprefix = {arXiv},...
RALL RGBmasking Aug16F 8B16F
This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set: Loss: 1.3708 Accuracy: 0.8012
ChronoDepth v1
This model represents the official checkpoint of the paper titled "Learning Temporally Consistent Video Depth from Video Diffusion Priors".
DamageTriageFormer Model
> Current revision checkpoint. This is the primary crop-mode model reported > in the revised manuscript. It was trained from scratch on the corrected > photo-atomic split, which keeps every tile from a source photo...
