diamond-in (💎 Ⓓ Ⓘ ⒶⓂⓄ Ⓝ Ⓓ💎)

reacted to tsungyi's post with 👍🔥 4 days ago

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2610

🎉 Exciting News — NVIDIA Cosmos is celebrating its 1st birthday and has hit 5 MILLION downloads! 🎉

In just one year, the Cosmos ecosystem has grown rapidly:
🧠 Cosmos Reason and Cosmos Predict have surpassed 2 MILLION downloads each on @HuggingFace , topping physical AI leaderboards
🔄 Cosmos Transfer is enabling adaptation across domains and tasks
🔮 Cosmos Cookbook is the go-to hub for recipes from developers and partners like Uber and IntBot.

Thank you to our amazing developer community for making this possible. Here's to pushing the boundaries of world foundation models together!

🧑🏻‍🍳Read the Cosmos Cookbook: https://nvda.ws/4qevli8
📚 Explore Models & Datasets: https://huggingface.co/collections/nvidia/nvidia-cosmos-2

reacted to mitkox's post with 🚀 9 days ago

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3203

I just stress-tested the Beast: MiniMax-M2.1 on Z8 Fury G5.
2101 tokens/sec. FORTY concurrent clients. That's 609 t/s out, 1492 t/s in. The model outputs fire faster than I can type, but feeds on data like a black hole on cheat day.
But wait, there's more! Threw it into Claude Code torture testing with 60+ tools, 8 agents (7 sub-agents because apparently one wasn't enough chaos). It didn't even flinch. Extremely fast, scary good at coding. The kind of performance that makes you wonder if the model's been secretly reading Stack Overflow in its spare time lol
3 months ago, these numbers lived in my "maybe in “2030 dreams. Today it's running on my desk AND heaths my home office during the winter!

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reacted to MonsterMMORPG's post with ➕ 22 days ago

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3637

Wan 2.2 Complete Training Tutorial - Text to Image, Text to Video, Image to Video, Windows & Cloud : https://youtu.be/ocEkhAsPOs4

Wan 2.2 training is now so easy. I have done over 64 different unique Wan 2.2 trainings to prepare the very best working training configurations for you. The configurations are fully working locally with as low as 6 GB GPUs. So you will be able to train your awesome Wan 2.2 image or video generation LoRAs on your Windows computer with easiness. Moreover, I have shown how to train on cloud platforms RunPod and Massed Compute so even if you have no GPU or you want faster training, you can train on cloud for very cheap prices fully privately.

Full step by step tutorial : https://youtu.be/ocEkhAsPOs4

⏱️ Video Chapters:

0:00 Introduction to Wan 2.2 Training & Capabilities
0:56 Installing & Updating Musubi Tuner Locally
2:20 Explanation of Optimized Presets & Research Logic
4:00 Differences Between T2I, T2V, and I2V Configs
5:36 Extracting Files & Running Update Batch File
6:14 Downloading Wan 2.2 Training Models via Script
7:30 Loading Configs: Selecting GPU & VRAM Options
9:33 Using nvitop to Monitor RAM & VRAM Usage
10:28 Preparing Image Dataset & Trigger Words
11:17 Generating Dataset Config & Resolution Logic
12:55 Calculating Epochs & Checkpoint Save Frequency
13:40 Troubleshooting: Fixing Missing VAE Path Error
15:12 VRAM Cache Behavior & Training Speed Analysis
15:51 Trade-offs: Learning Rate vs Resolution vs Epochs
16:29 Installing SwarmUI & Updating ComfyUI Backend
18:13 Importing Latest Presets into SwarmUI
19:25 Downloading Inference Models via Script
20:33 Generating Images with Trained Low Noise LoRA
22:22 Upscaling Workflow for High-Fidelity Results
24:15 Increasing Base Resolution to 1280x1280
27:26 Text-to-Video Generation with Lightning LoRA
30:12 Image-to-Video Generation Workflow & Settings
31:35 Restarting Backend to Clear VRAM for Model Switching
33:45 Fixing RAM Crashes with Cache-None Argument
....

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reacted to prithivMLmods's post with 👍 about 1 month ago

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1139

Try CUA GUI Operator 🖥️ Space, the demo of some interesting multimodal ultra-compact Computer Use Agent (CUA) models in a single app, including Fara-7B, UI-TARS-1.5-7B, and Holo models, to perform GUI localization tasks.

● CUA-GUI-Operator [Demo]: prithivMLmods/CUA-GUI-Operator
● Collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations

Other related multimodal spaces

● Qwen3-VL: prithivMLmods/Qwen3-VL-HF-Demo
● Multimodal-VLM-v1.0: prithivMLmods/Multimodal-VLM-v1.0
● Vision-to-VibeVoice-en: prithivMLmods/Vision-to-VibeVoice-en

I have planned to add Chrome sandboxes to streamline it and turn it into a browser based CUA multimodal tool, which will be added to the same space soon.

To know more about it, visit the app page or the respective model page!

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posted an update about 1 month ago

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Introducing Browser-Use-mcp for llm models.
It is all started from one problem that i faced in chatgpt , that if you are on free plan then they do not allow you to use the agent model so i made this which will work as chatgpt agent mode works( can click object, read text , etc in website ).
I hope you all will like this space.

Space Url: diamond-in/Browser-Use-mcp

Thank you,
@diamond-in

reacted to samihalawa's post with 🚀 7 months ago

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2542

🔥BEST DEBUG PROMPT FOR CLAUDE_CODE
😲FIXES ANY REPO

How can I prompt you so there will not be any More bug or thing? So list the 20 kind of errors and bugs more common in a codebase like this one and create a comprehensive table list of each of them and all the main files and fucnionality and fix until cross all out. Don't add complexity. Ignore security. Only fatal problems
Proceed in the most exhaustive and comprehensive way possible. Don't miss a line of code. SYSTEMATICALLY FIX EVERYTHING

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