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dylanebert 
posted an update 10 days ago
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1029
📢 New #1 in Generative 3D

CSM/Cube from Common Sense Machines is now the top ranked image-to-3d model

check out the results in dylanebert/3d-arena
regisss 
posted an update 23 days ago
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1646
Nice paper comparing the fp8 inference efficiency of Nvidia H100 and Intel Gaudi2: An Investigation of FP8 Across Accelerators for LLM Inference (2502.01070)

The conclusion is interesting: "Our findings highlight that the Gaudi 2, by leveraging FP8, achieves higher throughput-to-power efficiency during LLM inference"

One aspect of AI hardware accelerators that is often overlooked is how they consume less energy than GPUs. It's nice to see researchers starting carrying out experiments to measure this!

Gaudi3 results soon...
dylanebert 
posted an update about 1 month ago
dylanebert 
posted an update about 1 month ago
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683
⚙️ Convert .ply to .splat

i've created a simple space to convert .ply gaussian splat files to .splat format

dylanebert/ply-to-splat
dylanebert 
posted an update about 2 months ago
akhaliq 
posted an update 3 months ago
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12640
Google drops Gemini 2.0 Flash Thinking

a new experimental model that unlocks stronger reasoning capabilities and shows its thoughts. The model plans (with thoughts visible), can solve complex problems with Flash speeds, and more

now available in anychat, try it out: akhaliq/anychat
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regisss 
posted an update 3 months ago
dylanebert 
posted an update 3 months ago
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2312
TRELLIS is now the highest ranked open-source model in the 3D Arena Leaderboard, surpassing InstantMesh

dylanebert/3d-arena
  • 1 reply
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dylanebert 
posted an update 3 months ago
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2923
blender has AI now
dylanebert 
posted an update 3 months ago
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4503
🟦 New open-source Image-to-3D model from Microsoft

TRELLIS: Structured 3D Latents for Scalable and Versatile 3D Generation

it's really good! the topology isn't clean, but it's a very very good 3D reference

JeffreyXiang/TRELLIS-image-large
  • 1 reply
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akhaliq 
posted an update 3 months ago
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13201
QwQ-32B-Preview is now available in anychat

A reasoning model that is competitive with OpenAI o1-mini and o1-preview

try it out: akhaliq/anychat
  • 1 reply
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akhaliq 
posted an update 3 months ago
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4210
New model drop in anychat

allenai/Llama-3.1-Tulu-3-8B is now available

try it here: akhaliq/anychat
dylanebert 
posted an update 3 months ago
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1668
Generate meshes with AI locally in Blender

📢 New open-source release

meshgen, a local blender integration of LLaMa-Mesh, is open source and available now 🤗

get started here: https://github.com/huggingface/meshgen
akhaliq 
posted an update 4 months ago
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3119
anychat

supports chatgpt, gemini, perplexity, claude, meta llama, grok all in one app

try it out there: akhaliq/anychat
regisss 
posted an update 5 months ago
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1419
Interested in performing inference with an ONNX model?⚡️

The Optimum docs about model inference with ONNX Runtime is now much clearer and simpler!

You want to deploy your favorite model on the hub but you don't know how to export it to the ONNX format? You can do it in one line of code as follows:
from optimum.onnxruntime import ORTModelForSequenceClassification

# Load the model from the hub and export it to the ONNX format
model_id = "distilbert-base-uncased-finetuned-sst-2-english"
model = ORTModelForSequenceClassification.from_pretrained(model_id, export=True)

Check out the whole guide 👉 https://huggingface.co./docs/optimum/onnxruntime/usage_guides/models
dylanebert 
posted an update 5 months ago
dylanebert 
posted an update 6 months ago
dylanebert 
posted an update 6 months ago
dylanebert 
posted an update 6 months ago
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2557
Here's a 1-minute video tutorial on how to fine-tune unsloth/llama-3-8b-bnb-4bit with unsloth

Using Roller Coaster Tycoon peep thoughts as an example
akhaliq 
posted an update 9 months ago
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20815
Phased Consistency Model

Phased Consistency Model (2405.18407)

The consistency model (CM) has recently made significant progress in accelerating the generation of diffusion models. However, its application to high-resolution, text-conditioned image generation in the latent space (a.k.a., LCM) remains unsatisfactory. In this paper, we identify three key flaws in the current design of LCM. We investigate the reasons behind these limitations and propose the Phased Consistency Model (PCM), which generalizes the design space and addresses all identified limitations. Our evaluations demonstrate that PCM significantly outperforms LCM across 1--16 step generation settings. While PCM is specifically designed for multi-step refinement, it achieves even superior or comparable 1-step generation results to previously state-of-the-art specifically designed 1-step methods. Furthermore, we show that PCM's methodology is versatile and applicable to video generation, enabling us to train the state-of-the-art few-step text-to-video generator.