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How smoking every day year after year affects your lungs visualized in 3D using GPT 6 Astra 🫁 Nah, that’s not 10 different models there or any shady dark magic. It’s just ONE model that I built using Tripo. Astra worked directly on that glb model using Three.js, added...

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The Bugged Dev

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71,990 просмотров • 8 дней назад •via X (Twitter)

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Комментарии: 17

Фото профиля Aditya
Aditya8 дней назад

@tripoai @threejs Astra is just amazing

Фото профиля The Bugged Dev
The Bugged Dev8 дней назад

@tripoai @threejs As of now, yes :D

Фото профиля Ganesh
Ganesh7 дней назад

@tripoai @threejs Looks sick man! 🔥 How many tokens used? How much does it roughly cost to generate something like this?

Фото профиля The Bugged Dev
The Bugged Dev7 дней назад

@tripoai @threejs I'm on 5x Pro plan, it took around 5-10% of that session. You should be comfortably able to build such 10-15 applications in a single weekly session of pro plan

Фото профиля Ganesh
Ganesh7 дней назад

@tripoai @threejs Thanks for giving me the rough estimates.

Фото профиля Yun Huang
Yun Huang7 дней назад

@tripoai @threejs the capability of astra is insane, wondering how accurate they are though

Фото профиля The Bugged Dev
The Bugged Dev7 дней назад

@tripoai @threejs I had put it through multiple rounds of research so it should be near accurate at least

Фото профиля Ali
Ali8 дней назад

@tripoai @threejs Bruv what is your endgame you keep making cool 3D models for a living ?

Фото профиля The Bugged Dev
The Bugged Dev8 дней назад

@tripoai @threejs I do it for fun mainly because these are websites I wanted to build on my own but couldn't before for so-so reasons

Фото профиля Ali
Ali8 дней назад

@tripoai @threejs I suppose you start saving these assets and build a library will be helpful for you when AR and VR apps become mainstream.

Фото профиля The Bugged Dev
The Bugged Dev8 дней назад

@tripoai @threejs Of course, these will be much more efficient with AR/VR. I'm planning to open source my 3D asset library soon too

Фото профиля Alek
Alek8 дней назад

@tripoai @threejs same on one tripo model tbh

Фото профиля The Bugged Dev
The Bugged Dev8 дней назад

@tripoai @threejs

Фото профиля Sebastian Buzdugan
Sebastian Buzdugan7 дней назад

@tripoai @threejs one glb reduces drift, but morph targets make year transitions easier to test

Фото профиля Victor
Victor7 дней назад

@tripoai @threejs Did you put it on GitHub?

Фото профиля Juan Diaz Mochon
Juan Diaz Mochon7 дней назад

@tripoai @threejs @banavarrete

Фото профиля St1mul
St1mul7 дней назад

@tripoai @threejs This is genuinely one of the best uses of AI I've seen this week — turning "smoking is bad for you" into something you can actually see happening in real time. The 3D morph + TSL shader approach is such a smart way to make abstract health data visceral. 🫁

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This AI created an interactive 3D textbook !! 💀 I didn't manually create any of these 3d models I built it using: 👉 GPT-6 Astra 👉 Hyper3D Rodin's MCP Hyper3D worked on the 3D Models And GPT-6 Astra made the website with the 3D Models integrated to the UI controls. It even added floating labels for the HEART !! This is what happens when an AI can actually CREATE 3D assets 👇
0:27

This AI created an interactive 3D textbook !! 💀 I didn't manually create any of these 3d models I built it using: 👉 GPT-6 Astra 👉 Hyper3D Rodin's MCP Hyper3D worked on the 3D Models And GPT-6 Astra made the website with the 3D Models integrated to the UI controls. It even added floating labels for the HEART !! This is what happens when an AI can actually CREATE 3D assets 👇

SARAH

135,934 просмотров • 4 дней назад

Probably I vibe coded a lil startup here? 😭 It has been such a loooong wish of mine to build some kind of 3D experience where I could customize a T-shirt in literally any way possible and it’s finally here. Built with Three.js using GPT 6 Astra, this is a full 3D T-shirt customization studio where you can visualize and customize a realistic shirt directly in the browser. That T-shirt itself was modeled by Astra using Tripo right inside Codex through Tripo Plugin. And you can pretty much do anything with it. You can paint directly on any side of the shirt using different brushes and colors, or even spray paint it in real time just like you would spray on a wall. There are also stickers generated using GPT Image 2.5 that you can place anywhere on the T-shirt, resize, reposition, recolor, layer, and customize however you want. On top of that, there’s support for things like fabric customization, sizing, layers, colors, and even wind simulation to push the realism a little further. Once you’re done, you can export the entire design as a 3D view or export individual images of the T-shirt so you could technically take the design, print it, and maybe even sell it. One of my favorite parts is how the spray painting effect works directly on the 3D T-shirt in real time. I also loved seeing how Astra managed to keep the whole experience performant across devices using a custom BVH implementation along with several CPU side optimizations. And the process of building it was super simple. I generated the initial studio design using GPT Image 2.5, gave that image to Astra with the Tripo Plugin enabled, and it basically handled everything from there. I didn’t have to separately generate a 3D reference, upload it to Tripo, download the asset, give it back to Astra, or manually coordinate any of that. Astra handled the entire flow on its own without needing any additional input from me. Really happy with both the process and how the final result turned out. Live:
1:04

Probably I vibe coded a lil startup here? 😭 It has been such a loooong wish of mine to build some kind of 3D experience where I could customize a T-shirt in literally any way possible and it’s finally here. Built with Three.js using GPT 6 Astra, this is a full 3D T-shirt customization studio where you can visualize and customize a realistic shirt directly in the browser. That T-shirt itself was modeled by Astra using Tripo right inside Codex through Tripo Plugin. And you can pretty much do anything with it. You can paint directly on any side of the shirt using different brushes and colors, or even spray paint it in real time just like you would spray on a wall. There are also stickers generated using GPT Image 2.5 that you can place anywhere on the T-shirt, resize, reposition, recolor, layer, and customize however you want. On top of that, there’s support for things like fabric customization, sizing, layers, colors, and even wind simulation to push the realism a little further. Once you’re done, you can export the entire design as a 3D view or export individual images of the T-shirt so you could technically take the design, print it, and maybe even sell it. One of my favorite parts is how the spray painting effect works directly on the 3D T-shirt in real time. I also loved seeing how Astra managed to keep the whole experience performant across devices using a custom BVH implementation along with several CPU side optimizations. And the process of building it was super simple. I generated the initial studio design using GPT Image 2.5, gave that image to Astra with the Tripo Plugin enabled, and it basically handled everything from there. I didn’t have to separately generate a 3D reference, upload it to Tripo, download the asset, give it back to Astra, or manually coordinate any of that. Astra handled the entire flow on its own without needing any additional input from me. Really happy with both the process and how the final result turned out. Live:

The Bugged Dev

47,645 просмотров • 5 дней назад

Can GPT-6 Astra actually create a 3D model like this? 🤔 I’ve been seeing people hype GPT-6 Astra looooot when it comes to 3D modeling, but can it really create 3D models with this level of detail? Wish i had access to try it,.. anyway, I created this one using Tripo as my lil submission to Tripo’s Companion Challenge where you have to create a 3D companion of your choice. I generated a bunch of different imaginary companions using GPT Image 2.0, from cute little dragons and humans to these adorable animals. After trying out a lot of different ideas, I finally settled on this panda in a bamboo forest look. I love how quickly you can go from having a random idea in your head to actually seeing it come to life, these days. That part is honestly so much fun. Now I just need to animate this little guy and turn it into an animated panda game or maybe 3D print it out haha #tripop2
0:28

Can GPT-6 Astra actually create a 3D model like this? 🤔 I’ve been seeing people hype GPT-6 Astra looooot when it comes to 3D modeling, but can it really create 3D models with this level of detail? Wish i had access to try it,.. anyway, I created this one using Tripo as my lil submission to Tripo’s Companion Challenge where you have to create a 3D companion of your choice. I generated a bunch of different imaginary companions using GPT Image 2.0, from cute little dragons and humans to these adorable animals. After trying out a lot of different ideas, I finally settled on this panda in a bamboo forest look. I love how quickly you can go from having a random idea in your head to actually seeing it come to life, these days. That part is honestly so much fun. Now I just need to animate this little guy and turn it into an animated panda game or maybe 3D print it out haha #tripop2

The Bugged Dev

160,498 просмотров • 12 дней назад

everybody talks about building AI automations but no one talks about how to evaluate if they’re actually working — especially at scale that’s why I put together a practical walkthrough on how to track AI performance in real-time using live dashboards inside, I cover: - context relevance: is the AI actually using what we give it? - gap detection: where your knowledge base is falling short - tracking: how to log and monitor outputs across any AI system - hallucination checks: flagging when the model starts making stuff up reply “track” and I’ll send it to you (must be following so I can DM)
0:28

everybody talks about building AI automations but no one talks about how to evaluate if they’re actually working — especially at scale that’s why I put together a practical walkthrough on how to track AI performance in real-time using live dashboards inside, I cover: - context relevance: is the AI actually using what we give it? - gap detection: where your knowledge base is falling short - tracking: how to log and monitor outputs across any AI system - hallucination checks: flagging when the model starts making stuff up reply “track” and I’ll send it to you (must be following so I can DM)

Tyler

21,627 просмотров • 1 год назад

Goddamn, GPT-6 Astra is something really Astraordinary 😱 I gave it a 3D model and asked it to auto rig the character and add animations like walking, running and a few Kung Fu moves... and IT ACTUALLY DID IT!! No big prompts or anything. Just simple trash talk mentioning what to do. Okay, wait wait wait. Welcome to the dark reality. It took me 3 sessions to get this result and somewhere it is still very much broken 😂 But this is genuinely a great step forward for the 3D modeling field. I had tried rigging the same model using Kimi K3 and the results were bad. Almost awful. So far, Astra does feel much more promising than the other models I have tested so far. More tests coming
0:29

Goddamn, GPT-6 Astra is something really Astraordinary 😱 I gave it a 3D model and asked it to auto rig the character and add animations like walking, running and a few Kung Fu moves... and IT ACTUALLY DID IT!! No big prompts or anything. Just simple trash talk mentioning what to do. Okay, wait wait wait. Welcome to the dark reality. It took me 3 sessions to get this result and somewhere it is still very much broken 😂 But this is genuinely a great step forward for the 3D modeling field. I had tried rigging the same model using Kimi K3 and the results were bad. Almost awful. So far, Astra does feel much more promising than the other models I have tested so far. More tests coming

The Bugged Dev

48,598 просмотров • 11 дней назад

Live: Source: You can download this to start your scenes with #r3f, #threejs WebGPU Renderer, and Post-Processing using #tsl. I also converted my jet engine shader from GLSL to TSL using the transpiler. It works like a dream😍. I added the Royal Naboo starship in the scene to show how Screen Space Reflections reacts to all metallic surfaces, not just the floor. I hope you like it. Please give me a star⭐️on GitHub if you can. #threejsJourney
1:27

Live: Source: You can download this to start your scenes with #r3f, #threejs WebGPU Renderer, and Post-Processing using #tsl. I also converted my jet engine shader from GLSL to TSL using the transpiler. It works like a dream😍. I added the Royal Naboo starship in the scene to show how Screen Space Reflections reacts to all metallic surfaces, not just the floor. I hope you like it. Please give me a star⭐️on GitHub if you can. #threejsJourney

Anderson Mancini

20,268 просмотров • 1 год назад

Here's a look behind the scenes of how I used a 3d model, generated from an image, as a "driver" for ai animation. In the near future we'll see more 3d tools that support these types of workflows, with much more emphasis on enhancing user input instead of just letting the ai do everything. I used the 3d model to generate keyframes that I then animated in Luma Dream. By using a 3d model with a diffusion "layer" done with Krea, I got quite high quality frames with a relatively high consistency as well since the AI didn't have to "hallucinate" that much. I upscaled and detailed the frames using Magnific. Using semi-detailed 3d models as drivers for gen ai is very powerful, and it allows us to use models that are sculpted in a more free-flowing type of workflow that doesn't rely so much on high surface detailing or very time-consuming finish, but instead relies more on gestural 3d sculpting. #art #ai
0:24

Here's a look behind the scenes of how I used a 3d model, generated from an image, as a "driver" for ai animation. In the near future we'll see more 3d tools that support these types of workflows, with much more emphasis on enhancing user input instead of just letting the ai do everything. I used the 3d model to generate keyframes that I then animated in Luma Dream. By using a 3d model with a diffusion "layer" done with Krea, I got quite high quality frames with a relatively high consistency as well since the AI didn't have to "hallucinate" that much. I upscaled and detailed the frames using Magnific. Using semi-detailed 3d models as drivers for gen ai is very powerful, and it allows us to use models that are sculpted in a more free-flowing type of workflow that doesn't rely so much on high surface detailing or very time-consuming finish, but instead relies more on gestural 3d sculpting. #art #ai

Martin Nebelong

48,280 просмотров • 2 лет назад

How many of you actually know how "what you eat" grows? 🤔 I never learned crop science in school. I learned it by walking around our farm with my father, who showed me different crops and explained how they grow. But not everyone has access to a farm, so I built a 3D Crop Science application in Three.js using Claude Opus 5 to make that learning experience more visual and interactive. It is an exploration of different types of seeds where each seed has three different stages. The first stage shows the whole seed. The second stage is a cross section that shows what is inside the seed and how it grows. The third stage shows the germination phase through a 3D model. There are 24 models in total. The original models were 1,349.6 MB, which Claude optimized down to just 11.6 MB in total. All of the 3D models were generated using Tripo. Claude also created visual information for each seed showing details like seed type, storage tissue and germination phase. Each seed also has a YouTube video that shows how it actually grows in the real world. There is also a section showing where each seed is commonly grown using both a 3D globe and a flat map. You can explore different regions and click on specific areas to see more information about where that seed is grown. The entire experience is fully responsive and also includes quizzes that you can take in both normal and 3D formats. I strongly believe education becomes much more effective when you can see, interact, watch and explore instead of relying only on textbooks. Live: Code:
1:14

How many of you actually know how "what you eat" grows? 🤔 I never learned crop science in school. I learned it by walking around our farm with my father, who showed me different crops and explained how they grow. But not everyone has access to a farm, so I built a 3D Crop Science application in Three.js using Claude Opus 5 to make that learning experience more visual and interactive. It is an exploration of different types of seeds where each seed has three different stages. The first stage shows the whole seed. The second stage is a cross section that shows what is inside the seed and how it grows. The third stage shows the germination phase through a 3D model. There are 24 models in total. The original models were 1,349.6 MB, which Claude optimized down to just 11.6 MB in total. All of the 3D models were generated using Tripo. Claude also created visual information for each seed showing details like seed type, storage tissue and germination phase. Each seed also has a YouTube video that shows how it actually grows in the real world. There is also a section showing where each seed is commonly grown using both a 3D globe and a flat map. You can explore different regions and click on specific areas to see more information about where that seed is grown. The entire experience is fully responsive and also includes quizzes that you can take in both normal and 3D formats. I strongly believe education becomes much more effective when you can see, interact, watch and explore instead of relying only on textbooks. Live: Code:

The Bugged Dev

45,081 просмотров • 24 дней назад

GPT-6-Astra has solved Onshape by PTC for me 😎 it's been building a robot using the sensors i've chosen; i simply dictate to codex what changes i want, and then watch in real-time while it makes them happen in CAD this is ridiculous lol btw that's me controlling the mouse & model views while codex works from the backend using a connector that it built
0:44

GPT-6-Astra has solved Onshape by PTC for me 😎 it's been building a robot using the sensors i've chosen; i simply dictate to codex what changes i want, and then watch in real-time while it makes them happen in CAD this is ridiculous lol btw that's me controlling the mouse & model views while codex works from the backend using a connector that it built

alpha_rover

41,351 просмотров • 11 дней назад

If you’re not using AI to build apps, you’re not going to make it The real question isn’t “Should I use AI?” It’s: → which model → and how you use it Using + Opus 4.5, I’ve been building Flow State with just a few prompts Almost ready for App Store approval Update #3 below Built entirely on my iPhone from a hot tub in Miami And every time I got distracted, Rork pulled me back with a notification Building has changed forever Don’t be like those business that never adapted to the internet and were forced to close their doors
1:05

If you’re not using AI to build apps, you’re not going to make it The real question isn’t “Should I use AI?” It’s: → which model → and how you use it Using + Opus 4.5, I’ve been building Flow State with just a few prompts Almost ready for App Store approval Update #3 below Built entirely on my iPhone from a hot tub in Miami And every time I got distracted, Rork pulled me back with a notification Building has changed forever Don’t be like those business that never adapted to the internet and were forced to close their doors

Jah Jiren

31,802 просмотров • 8 месяцев назад

GPT-4o is bad at processing PDF documents. Whoever tells you otherwise is not living in the real world. In 2024, people fill out forms using pen and paper. Try to answer questions from those forms using modern models, and you'll be disappointed. I recorded a video to show you how to fix this. The answer is simple: stop letting the model see your PDF document. Instead, preprocess it and stick to showing the model text. Watch the video. You'll go from "THIS IS CRAP" to "EXCELLENT" in no time. I'm using Unstract to turn the documents into text while keeping the original format (this is crucial!) You can use them to process up to 100 pages for free. They collaborated with me on this post. You can find the code I wrote right here:
6:27

GPT-4o is bad at processing PDF documents. Whoever tells you otherwise is not living in the real world. In 2024, people fill out forms using pen and paper. Try to answer questions from those forms using modern models, and you'll be disappointed. I recorded a video to show you how to fix this. The answer is simple: stop letting the model see your PDF document. Instead, preprocess it and stick to showing the model text. Watch the video. You'll go from "THIS IS CRAP" to "EXCELLENT" in no time. I'm using Unstract to turn the documents into text while keeping the original format (this is crucial!) You can use them to process up to 100 pages for free. They collaborated with me on this post. You can find the code I wrote right here:

Santiago

196,861 просмотров • 2 лет назад

"Hey Astra, make me a Mac app. It should render a 3D iPod that you'll build in Blender, then using the original iPod UI and interactions I want to be able to visualize all my Codex threads on it." 15 minutes later: Boom. What's even in this model? What time we're living in!??
0:35

"Hey Astra, make me a Mac app. It should render a 3D iPod that you'll build in Blender, then using the original iPod UI and interactions I want to be able to visualize all my Codex threads on it." 15 minutes later: Boom. What's even in this model? What time we're living in!??

Pietro Schirano

685,890 просмотров • 12 дней назад

You don't need to be a 3D artist to start building 3D websites anymore 💛 Built this cool 3D jet drone website in Three.js using Claude Opus 5 and Tripo 🔜 gamescom in < 1 hour. A lot of people still think AI is great for generating code, but not for building something that actually feels polished and interactive or "complex". But it has been changing super fast these days. The model you see here is only 946KB, compressed from its original 13.6MB size automatically by Claude without losing any quality. This kind of intelligence has been developed in many other AI tools for anything related to 3D (except GPT 5.6 sol lol). You just have to describe what you want and they handle everything "engineerly" (that's not even a word but okay :D) Anyway, also you don't really have to learn anything about 3D modeling to create these models. All you need is a good image and put it in Tripo. For this case, i generated model using "smart mesh" feature that generated a cleaner low-poly topology and edge flow. That helps keep your actual 3D asset even more lightweight. Earlier, with HD model feature, my model size with 8k texture was around 60-70MB but with Smart Mesh, it's around 13-16MB with 8k texture applied separately. Of course, this isn't something I knew from the beginning. All I did was "try" out different features and see what happens. Live: Code: Design:
0:27

You don't need to be a 3D artist to start building 3D websites anymore 💛 Built this cool 3D jet drone website in Three.js using Claude Opus 5 and Tripo 🔜 gamescom in < 1 hour. A lot of people still think AI is great for generating code, but not for building something that actually feels polished and interactive or "complex". But it has been changing super fast these days. The model you see here is only 946KB, compressed from its original 13.6MB size automatically by Claude without losing any quality. This kind of intelligence has been developed in many other AI tools for anything related to 3D (except GPT 5.6 sol lol). You just have to describe what you want and they handle everything "engineerly" (that's not even a word but okay :D) Anyway, also you don't really have to learn anything about 3D modeling to create these models. All you need is a good image and put it in Tripo. For this case, i generated model using "smart mesh" feature that generated a cleaner low-poly topology and edge flow. That helps keep your actual 3D asset even more lightweight. Earlier, with HD model feature, my model size with 8k texture was around 60-70MB but with Smart Mesh, it's around 13-16MB with 8k texture applied separately. Of course, this isn't something I knew from the beginning. All I did was "try" out different features and see what happens. Live: Code: Design:

The Bugged Dev

49,863 просмотров • 1 месяц назад

Your our history shouldn’t be taught in a boring way 🫠 I’ve always loved history, but I could never imagine what life actually looked like back then. So I built Empire Atlas, a 3D interactive explorer of 8 historical empires using Three.js and Kimi.ai K3 🔥 It lets you explore how people lived, what their homes looked like, their maps, daily life, interiors, and more. Properly researched. But the craziest part is that this was near one shot vibe coded with Kimi K3 🤯 When I previously built a 3D anatomy app with GPT 5.6 sol, I had to iterate on performance and optimization. With Kimi, the moment I handed over the 3D assets (generated using Tripo), prompt and design (by GPT Image 2.0), it created an 11 step engineering plan to build the entire thing. The very first step it did was optimizing the assets. It took nearly 500MB of 3D assets and brought them down to just 17.8MB using mesh simplification, Draco compression, and 1024px WebP textures. Absolutely nuts. It also generated 56 historical images across the 8 empires showing daily life, maps, interiors, and more using its image plugin with batch processing. Those were converted to WebP too, bringing the total image size to around 10MB. That’s a huge reason the experience loads so fast on website. It's engineering workflow or intelligence has really impressed me so far. The only downside is that it took more than 5 hours, though 😅 Anyway, back to history. In Empire Atlas, you can explore 8 different empires and see how people and our ancestors lived at that time. I really love those textures I was able to create using Tripo. You can explore their homes in 3D, and there’s so much more we could do with this. We could extend these houses into fully explorable interiors and create increasingly realistic reconstructions of what life actually looked like. And maybe create fun education games too. I genuinely think this can make history education so much more immersive. Much more than showing black and white images in boring textbooks. Go explore your history now 👇 Live: Code:
0:43

Your our history shouldn’t be taught in a boring way 🫠 I’ve always loved history, but I could never imagine what life actually looked like back then. So I built Empire Atlas, a 3D interactive explorer of 8 historical empires using Three.js and Kimi.ai K3 🔥 It lets you explore how people lived, what their homes looked like, their maps, daily life, interiors, and more. Properly researched. But the craziest part is that this was near one shot vibe coded with Kimi K3 🤯 When I previously built a 3D anatomy app with GPT 5.6 sol, I had to iterate on performance and optimization. With Kimi, the moment I handed over the 3D assets (generated using Tripo), prompt and design (by GPT Image 2.0), it created an 11 step engineering plan to build the entire thing. The very first step it did was optimizing the assets. It took nearly 500MB of 3D assets and brought them down to just 17.8MB using mesh simplification, Draco compression, and 1024px WebP textures. Absolutely nuts. It also generated 56 historical images across the 8 empires showing daily life, maps, interiors, and more using its image plugin with batch processing. Those were converted to WebP too, bringing the total image size to around 10MB. That’s a huge reason the experience loads so fast on website. It's engineering workflow or intelligence has really impressed me so far. The only downside is that it took more than 5 hours, though 😅 Anyway, back to history. In Empire Atlas, you can explore 8 different empires and see how people and our ancestors lived at that time. I really love those textures I was able to create using Tripo. You can explore their homes in 3D, and there’s so much more we could do with this. We could extend these houses into fully explorable interiors and create increasingly realistic reconstructions of what life actually looked like. And maybe create fun education games too. I genuinely think this can make history education so much more immersive. Much more than showing black and white images in boring textbooks. Go explore your history now 👇 Live: Code:

The Bugged Dev

120,448 просмотров • 1 месяц назад

You can now fine-tune Llama 3 without writing a single line of code! We are moving at breakneck speed. I recorded a video to show you how to fine-tune any open-source model in a few minutes. I'm using a GPT capable of taking a problem and turning it into a fine-tuned model that will solve it. You don't have to write any code. You only need to explain to a GPT what problem you want to solve and tell it you want to use Llama 3. For example, "fine-tune Llama 3" or "deploy zephyr." It feels magic. The system will recommend a dataset and fine-tune the model for you. I'm using Monster API, a platform that specializes in making fine-tuning and deploying open-source models easy and fast. Their stack is well-optimized to maximize fine-tuning efficiency using techniques like Q-Lora and vLLM. They are behind the GPT. Here is what you need to do: 1. Create an account at 2. Load the GPT with the link below This is as simple as it gets. When you are done, you can click a button to deploy the model and start using it. I have 10,000 free credits for anyone using the code "SANTIAGO" in the dashboard. You can use these credits to access, fine-tune, and deploy these open-source models. You can also keep up with their latest updates, and get free credits and special offers on their Discord server:
6:05

You can now fine-tune Llama 3 without writing a single line of code! We are moving at breakneck speed. I recorded a video to show you how to fine-tune any open-source model in a few minutes. I'm using a GPT capable of taking a problem and turning it into a fine-tuned model that will solve it. You don't have to write any code. You only need to explain to a GPT what problem you want to solve and tell it you want to use Llama 3. For example, "fine-tune Llama 3" or "deploy zephyr." It feels magic. The system will recommend a dataset and fine-tune the model for you. I'm using Monster API, a platform that specializes in making fine-tuning and deploying open-source models easy and fast. Their stack is well-optimized to maximize fine-tuning efficiency using techniques like Q-Lora and vLLM. They are behind the GPT. Here is what you need to do: 1. Create an account at 2. Load the GPT with the link below This is as simple as it gets. When you are done, you can click a button to deploy the model and start using it. I have 10,000 free credits for anyone using the code "SANTIAGO" in the dashboard. You can use these credits to access, fine-tune, and deploy these open-source models. You can also keep up with their latest updates, and get free credits and special offers on their Discord server:

Santiago

324,621 просмотров • 2 лет назад

To answer all the questions on how this works, the model is actually an image of a plushie that I split into layers and rigged like normal from there in Live2D. Here's a quick speed paint reference to show how the layers were made in CSP using photo manip strats 🧡
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To answer all the questions on how this works, the model is actually an image of a plushie that I split into layers and rigged like normal from there in Live2D. Here's a quick speed paint reference to show how the layers were made in CSP using photo manip strats 🧡

Clover🍀🐮🔜San Japan

104,111 просмотров • 1 год назад

Only if education could be this interactive ❤️‍🔥 I've had a looong wish to build something genuinely useful through vibe coding, and I finally did it. A 3D human anatomy application built with Three.js using GPT 5.6 Sol. It all started with a single design image that I created using GPT Image 2.0. I then used it to generate every 3D organ image, one by one. Next, I converted each of those images into 3D models using Tripo (and no, they didn't sponsor this 😄). After that, I opened Codex, wrote a master prompt based on the design, and gave it the prompt, the design image, and all the 3D models. Codex built the first version beautifully, but there was one big problem. Every single 3D model was nearly 120-150 MB. That obviously wasn't practical for the web and was giving a performance of 16fps. After a few iterations, Codex optimized each model down to roughly 2–5.5 MB while preserving the visual quality, reducing the total asset size from ~900 MB to just 28.6 MB. And each model loads on demand. Along the way, Codex also generated those anatomical illustrations showing where each organ sits in the human body, and even created the interactive hotspot markers that explain different parts of every organ. It handled all of that. The process wasn't exactly one shot, but it also wasn't difficult. You just have to do it step by step. It genuinely felt like building something that could make learning anatomy much more engaging. The inspiration came from Dilum Sanjaya's 3D animal plant cell project. I remember seeing it and thinking, "I want to build something like this one day." And I did it :D Live: Code:
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Only if education could be this interactive ❤️‍🔥 I've had a looong wish to build something genuinely useful through vibe coding, and I finally did it. A 3D human anatomy application built with Three.js using GPT 5.6 Sol. It all started with a single design image that I created using GPT Image 2.0. I then used it to generate every 3D organ image, one by one. Next, I converted each of those images into 3D models using Tripo (and no, they didn't sponsor this 😄). After that, I opened Codex, wrote a master prompt based on the design, and gave it the prompt, the design image, and all the 3D models. Codex built the first version beautifully, but there was one big problem. Every single 3D model was nearly 120-150 MB. That obviously wasn't practical for the web and was giving a performance of 16fps. After a few iterations, Codex optimized each model down to roughly 2–5.5 MB while preserving the visual quality, reducing the total asset size from ~900 MB to just 28.6 MB. And each model loads on demand. Along the way, Codex also generated those anatomical illustrations showing where each organ sits in the human body, and even created the interactive hotspot markers that explain different parts of every organ. It handled all of that. The process wasn't exactly one shot, but it also wasn't difficult. You just have to do it step by step. It genuinely felt like building something that could make learning anatomy much more engaging. The inspiration came from Dilum Sanjaya's 3D animal plant cell project. I remember seeing it and thinking, "I want to build something like this one day." And I did it :D Live: Code:

The Bugged Dev

2,099,103 просмотров • 1 месяц назад

img2threejs 1.5.1 is out 🚀 Checkout: This release introduces a new approach to image → 3D → Three.js. Image → Tripo → img2threejs → reconstructed geometry → Three.js Instead of using the generated 3D model as the final asset, img2threejs uses it as a reference to rebuild the character into a representation that can be generated and rendered directly in Three.js. No Blender workflow, and no GLB required as the final output. The animation in the demo is still a bit rough because this release is focused on reconstruction, not animation. I’ll be improving that in the next release. Still experimental, but this is a big step toward where I want img2threejs to go.
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img2threejs 1.5.1 is out 🚀 Checkout: This release introduces a new approach to image → 3D → Three.js. Image → Tripo → img2threejs → reconstructed geometry → Three.js Instead of using the generated 3D model as the final asset, img2threejs uses it as a reference to rebuild the character into a representation that can be generated and rendered directly in Three.js. No Blender workflow, and no GLB required as the final output. The animation in the demo is still a bit rough because this release is focused on reconstruction, not animation. I’ll be improving that in the next release. Still experimental, but this is a big step toward where I want img2threejs to go.

Nick

117,298 просмотров • 23 дней назад

SuperGrok is insanely powerful. Use the file chat feature and talk to your code in real time. Coded this 3D model of helmet for a game asset using threejs and webgl with Grok 4. The file chat allowed me to add lighting and color controls just like that. It felt surreal. Try it now.
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SuperGrok is insanely powerful. Use the file chat feature and talk to your code in real time. Coded this 3D model of helmet for a game asset using threejs and webgl with Grok 4. The file chat allowed me to add lighting and color controls just like that. It felt surreal. Try it now.

Prashant

1,274,168 просмотров • 1 год назад

What is really useful is how GPT-6 Astra got better in spatial understanding. I'm still shocked how good it navigates 3D space. Here I gave it Blender MCP and Tripo P2.0 to generate optimized 3D models and put them together, rig and animate. Result is freaking awesome! Doing 3D objects procedurally with Astra is fun, but quality is not compared with what 3D Gen can do. Like you don't ask GPT to draw image with pen when there is GPT Image, same here. And token cost also speaks for it, 3D gen simply cheaper. But the way it assemble thing together, characters and scene, that is shocking ngl. And rigging of course, I have so much hope on it, it is most annoying part of 3d for me lol
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What is really useful is how GPT-6 Astra got better in spatial understanding. I'm still shocked how good it navigates 3D space. Here I gave it Blender MCP and Tripo P2.0 to generate optimized 3D models and put them together, rig and animate. Result is freaking awesome! Doing 3D objects procedurally with Astra is fun, but quality is not compared with what 3D Gen can do. Like you don't ask GPT to draw image with pen when there is GPT Image, same here. And token cost also speaks for it, 3D gen simply cheaper. But the way it assemble thing together, characters and scene, that is shocking ngl. And rigging of course, I have so much hope on it, it is most annoying part of 3d for me lol

Stefan 3D AI

19,476 просмотров • 10 дней назад