Hugging Face
Hugging Face

Hugging Face

Hugging Face is a research organization and platform for machine learning. They cover topics like large language models, multimodal embeddings, and AI agent failures.

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Bringing Nunchaku 4-bit Diffusion Inference to Diffusers

Bringing Nunchaku 4-bit Diffusion Inference to Diffusers

2d

The original title is "The State of Simulation for Physical AI: An Overview"

The original title is "The State of Simulation for Physical AI: An Overview"

3d

Grabette: an open system to record robot-manipulation data

Grabette: an open system to record robot-manipulation data

4d

The original headline is: "NVIDIA Nemotron 3 Embed Ranks #1 Overall on RTEB, Advancing Agentic Retrieval"

The original headline is: "NVIDIA Nemotron 3 Embed Ranks #1 Overall on RTEB, Advancing Agentic Retrieval"

8d

What building Shippy taught us about building agents

What building Shippy taught us about building agents

9d

Introducing Real World VoiceEQ: Measuring the human quality of voice AI

Introducing Real World VoiceEQ: Measuring the human quality of voice AI

10d

Data for Agents

Data for Agents

16d

Run AI workloads on any cloud, store on Hugging Face: zero-egress storage with SkyPilot

Run AI workloads on any cloud, store on Hugging Face: zero-egress storage with SkyPilot

18d

1.  **Analyze the original title:** "Hugging Face and Cerebras bring Gemma 4 to real-time voice AI"

1. **Analyze the original title:** "Hugging Face and Cerebras bring Gemma 4 to real-time voice AI"

24d

The original title is 9 words: "ScarfBench: Benchmarking AI Agents for Enterprise Java Framework Migration"

The original title is 9 words: "ScarfBench: Benchmarking AI Agents for Enterprise Java Framework Migration"

24d

Hugging Face adds comprehensive eval results to model pages

Hugging Face adds comprehensive eval results to model pages

25d

The original title is: "DiScoFormer: One transformer for density and score, across distributions"

The original title is: "DiScoFormer: One transformer for density and score, across distributions"

25d

Run a vLLM Server on HF Jobs in One Command

Run a vLLM Server on HF Jobs in One Command

29d

Accelerating Transformers Fine-Tuning with NVIDIA NeMo AutoModel

Accelerating Transformers Fine-Tuning with NVIDIA NeMo AutoModel

30d

Build real agentic apps using CUGA: two dozen working examples on a lightweight harness

Build real agentic apps using CUGA: two dozen working examples on a lightweight harness

31d

Experimenting with the proposed Cross-Origin Storage API in Transformers.js

Experimenting with the proposed Cross-Origin Storage API in Transformers.js

32d

The original title is: "Shipping huggingface_hub every week with AI, open tools, and a human in the loop"

The original title is: "Shipping huggingface_hub every week with AI, open tools, and a human in the loop"

32d

PP-OCRv6 on Hugging Face: 50-Language OCR from 1.5M to 34.5M Parameters

PP-OCRv6 on Hugging Face: 50-Language OCR from 1.5M to 34.5M Parameters

32d

MosaicLeaks: Can your research agent keep a secret?

MosaicLeaks: Can your research agent keep a secret?

36d

Is it agentic enough? Benchmarking open models on your own tooling

Is it agentic enough? Benchmarking open models on your own tooling

37d

From the Hugging Face Hub to robot hardware with Strands Agents and LeRobot

From the Hugging Face Hub to robot hardware with Strands Agents and LeRobot

37d

Agentic Resource Discovery: Let agents search

Agentic Resource Discovery: Let agents search

38d

How an Agent Built a 3D Paris Gallery by Chaining Two Hugging Face Spaces

How an Agent Built a 3D Paris Gallery by Chaining Two Hugging Face Spaces

45d

Migrating Your GitHub CI to Hugging Face Jobs

Migrating Your GitHub CI to Hugging Face Jobs

46d