fal.ai
Kadir Nar PRO
kadirnar
AI & ML interests
Computer Vision, Open Source, Generative AI
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kadirnar's activity
replied to
their
post
10 days ago
replied to
their
post
11 days ago
fal.ai รผzerinden sync-lip var fakat onu kullanฤฑnca videonun kalitesi bozuluyor. Bu รงalฤฑลma da onu kullanmadฤฑm. Onu yaptฤฑฤฤฑm sesli bir รงalฤฑลma var. Fakat tts modellerinden iyi รงฤฑktฤฑ alamadฤฑm.
posted
an
update
11 days ago
Post
2650
I created my own AI image and video from scratch using the fal.ai platform ๐ซ
Workflow: Flux Lora Training + Upscale + Kling AI(1.6)
Workflow: Flux Lora Training + Upscale + Kling AI(1.6)
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- 5 replies
posted
an
update
5 months ago
Post
4278
I am training a controlnet model for Flux. And some of my experiences:
Checkpoint-10000:
https://x.com/kadirnar_ai/status/1829831750471606668
Checkpoint-12000:
https://x.com/kadirnar_ai/status/1829889524962640001
Checkpoint-14000:
https://x.com/kadirnar_ai/status/1829989622878744711
Checkpoint (16000-18000):
https://x.com/kadirnar_ai/status/1830179551407665654
Dataset: kadirnar/fluxdev_controlnet_16k
GPU: 1xA100(80GB)
GPU Hours: 65
Checkpoint-10000:
https://x.com/kadirnar_ai/status/1829831750471606668
Checkpoint-12000:
https://x.com/kadirnar_ai/status/1829889524962640001
Checkpoint-14000:
https://x.com/kadirnar_ai/status/1829989622878744711
Checkpoint (16000-18000):
https://x.com/kadirnar_ai/status/1830179551407665654
Dataset: kadirnar/fluxdev_controlnet_16k
GPU: 1xA100(80GB)
GPU Hours: 65
- 1 reply
posted
an
update
8 months ago
Post
4432
Stable Diffusion 3: Scaling Rectified Flow Transformers for High-Resolution Image Synthesis
Demo(Zero A100): kadirnar/Stable-Diffusion-3
Paper: https://arxiv.org/pdf/2403.03206
Model Page: stabilityai/stable-diffusion-3-medium
Thanks โค๏ธ @dn6 @sayakpaul
Demo(Zero A100): kadirnar/Stable-Diffusion-3
Paper: https://arxiv.org/pdf/2403.03206
Model Page: stabilityai/stable-diffusion-3-medium
Thanks โค๏ธ @dn6 @sayakpaul
posted
an
update
8 months ago
Post
3926
Fast Tachyon SDXL Demo:
Demo(Zero A100): kadirnar/BlackHole-Lightning
Model Page: https://civitai.com/models/414108/black-hole
Demo(Zero A100): kadirnar/BlackHole-Lightning
Model Page: https://civitai.com/models/414108/black-hole
reacted to
DmitryRyumin's
post with ๐ฅ
8 months ago
Post
1497
๐ฅ๐๐ New Research Alert - YOLOv10! ๐๐๐ฅ
๐ Title: YOLOv10: Real-Time End-to-End Object Detection ๐
๐ Description: YOLOv10 improves real-time object recognition by eliminating non-maximum suppression and optimizing the model architecture to achieve state-of-the-art performance with lower latency and computational overhead.
๐ฅ Authors: Ao Wang et al.
๐ Paper: YOLOv10: Real-Time End-to-End Object Detection (2405.14458)
๐ค Demo: kadirnar/Yolov10 curated by @kadirnar
๐ฅ Model ๐ค: kadirnar/Yolov10
๐ Repository: https://github.com/THU-MIG/yolov10
๐ฎ Post about YOLOv9 - https://huggingface.co/posts/DmitryRyumin/519784698531054
๐ More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
๐ Keywords: #YOLOv10 #ObjectDetection #RealTimeAI #ModelOptimization #MachineLearning #DeepLearning #ComputerVision #Innovation
๐ Title: YOLOv10: Real-Time End-to-End Object Detection ๐
๐ Description: YOLOv10 improves real-time object recognition by eliminating non-maximum suppression and optimizing the model architecture to achieve state-of-the-art performance with lower latency and computational overhead.
๐ฅ Authors: Ao Wang et al.
๐ Paper: YOLOv10: Real-Time End-to-End Object Detection (2405.14458)
๐ค Demo: kadirnar/Yolov10 curated by @kadirnar
๐ฅ Model ๐ค: kadirnar/Yolov10
๐ Repository: https://github.com/THU-MIG/yolov10
๐ฎ Post about YOLOv9 - https://huggingface.co/posts/DmitryRyumin/519784698531054
๐ More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
๐ Keywords: #YOLOv10 #ObjectDetection #RealTimeAI #ModelOptimization #MachineLearning #DeepLearning #ComputerVision #Innovation
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- 1 reply
replied to
DmitryRyumin's
post
8 months ago
Thanks๐ค
posted
an
update
8 months ago
Post
1911
BLACK HOLE SDXL Lightning:
Prompt: a photo of a baby dragon
Steps: 4
Prompt: a photo of a baby dragon
Steps: 4
replied to
their
post
9 months ago
Thanks ๐
reacted to
MonsterMMORPG's
post with ๐ฅโค๏ธ
10 months ago
Post
3694
Watch the full tutorial here : https://youtu.be/0t5l6CP9eBg
The tutorial is over 2 hours literally with manually fixed captions and perfect video chapters.
Most Awaited Full Fine Tuning (with DreamBooth effect) Tutorial Generated Images - Full Workflow Shared In The Comments - NO Paywall This Time - Explained OneTrainer - Cumulative Experience of 16 Months Stable Diffusion
In this tutorial, I am going to show you how to install OneTrainer from scratch on your computer and do a Stable Diffusion SDXL (Full Fine-Tuning 10.3 GB VRAM) and SD 1.5 (Full Fine-Tuning 7GB VRAM) based models training on your computer and also do the same training on a very cheap cloud machine from MassedCompute if you don't have such computer.
Tutorial Readme File โคต๏ธ
https://github.com/FurkanGozukara/Stable-Diffusion/blob/main/Tutorials/OneTrainer-Master-SD-1_5-SDXL-Windows-Cloud-Tutorial.md
Register Massed Compute From Below Link (could be necessary to use our Special Coupon for A6000 GPU for 31 cents per hour) โคต๏ธ
https://bit.ly/Furkan-Gรถzรผkara
Coupon Code for A6000 GPU is : SECourses
0:00 Introduction to Zero-to-Hero Stable Diffusion (SD) Fine-Tuning with OneTrainer (OT) tutorial
3:54 Intro to instructions GitHub readme
4:32 How to register Massed Compute (MC) and start virtual machine (VM)
5:48 Which template to choose on MC
6:36 How to apply MC coupon
8:41 How to install OT on your computer to train
9:15 How to verify your Python, Git, FFmpeg and Git installation
12:00 How to install ThinLinc and start using your MC VM
12:26 How to setup folder synchronization and file sharing between your computer and MC VM
13:56 End existing session in ThinClient
14:06 How to turn off MC VM
14:24 How to connect and start using VM
14:41 When use end existing session
16:38 How to download very best OT preset training configuration for SD 1.5 & SDXL models
18:00 How to load configuration preset
18:38 Full explanation of OT configuration and best hyper parameters for SDXL
.
.
.
The tutorial is over 2 hours literally with manually fixed captions and perfect video chapters.
Most Awaited Full Fine Tuning (with DreamBooth effect) Tutorial Generated Images - Full Workflow Shared In The Comments - NO Paywall This Time - Explained OneTrainer - Cumulative Experience of 16 Months Stable Diffusion
In this tutorial, I am going to show you how to install OneTrainer from scratch on your computer and do a Stable Diffusion SDXL (Full Fine-Tuning 10.3 GB VRAM) and SD 1.5 (Full Fine-Tuning 7GB VRAM) based models training on your computer and also do the same training on a very cheap cloud machine from MassedCompute if you don't have such computer.
Tutorial Readme File โคต๏ธ
https://github.com/FurkanGozukara/Stable-Diffusion/blob/main/Tutorials/OneTrainer-Master-SD-1_5-SDXL-Windows-Cloud-Tutorial.md
Register Massed Compute From Below Link (could be necessary to use our Special Coupon for A6000 GPU for 31 cents per hour) โคต๏ธ
https://bit.ly/Furkan-Gรถzรผkara
Coupon Code for A6000 GPU is : SECourses
0:00 Introduction to Zero-to-Hero Stable Diffusion (SD) Fine-Tuning with OneTrainer (OT) tutorial
3:54 Intro to instructions GitHub readme
4:32 How to register Massed Compute (MC) and start virtual machine (VM)
5:48 Which template to choose on MC
6:36 How to apply MC coupon
8:41 How to install OT on your computer to train
9:15 How to verify your Python, Git, FFmpeg and Git installation
12:00 How to install ThinLinc and start using your MC VM
12:26 How to setup folder synchronization and file sharing between your computer and MC VM
13:56 End existing session in ThinClient
14:06 How to turn off MC VM
14:24 How to connect and start using VM
14:41 When use end existing session
16:38 How to download very best OT preset training configuration for SD 1.5 & SDXL models
18:00 How to load configuration preset
18:38 Full explanation of OT configuration and best hyper parameters for SDXL
.
.
.
reacted to
DmitryRyumin's
post with ๐คโค๏ธ
11 months ago
Post
๐โจ Exciting Research Alert! YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information ๐
YOLOv9 is the latest breakthrough in object detection!
๐ Title: YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
๐ฅ Authors: Chien-Yao Wang et al.
๐ Published: ArXiv, February 2024
๐ Paper: YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information (2402.13616)
๐ Model ๐ค: adonaivera/yolov9
๐ Repo: https://github.com/WongKinYiu/yolov9
๐ Don't miss out on this cutting-edge research! Explore YOLOv9 today and stay ahead of the curve in the dynamic world of computer vision. ๐
๐ Keywords: #YOLOv9 #ObjectDetection #DeepLearning #ComputerVision #Innovation #Research #ArtificialIntelligence
YOLOv9 is the latest breakthrough in object detection!
๐ Title: YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
๐ฅ Authors: Chien-Yao Wang et al.
๐ Published: ArXiv, February 2024
๐ Paper: YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information (2402.13616)
๐ Model ๐ค: adonaivera/yolov9
๐ Repo: https://github.com/WongKinYiu/yolov9
๐ Don't miss out on this cutting-edge research! Explore YOLOv9 today and stay ahead of the curve in the dynamic world of computer vision. ๐
๐ Keywords: #YOLOv9 #ObjectDetection #DeepLearning #ComputerVision #Innovation #Research #ArtificialIntelligence
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- 1 reply
replied to
DmitryRyumin's
post
11 months ago
I developed the package code for the Yolov9 model.
reacted to
merve's
post with โค๏ธ
12 months ago
Post
There's a new leaderboard for vision language models ๐คฉ
The models are ranked based on ELO, you can rate the responses to preselected examples or try with your input ๐ค
WildVision/vision-arena
The models are ranked based on ELO, you can rate the responses to preselected examples or try with your input ๐ค
WildVision/vision-arena