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Democratizar el PLN en español creando recursos abiertos en nuestro idioma🚀

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mariagrandury  authored a paper 15 days ago
BabyBabelLM: A Multilingual Benchmark of Developmentally Plausible Training Data
mariagrandury  authored a paper 15 days ago
Measuring what Matters: Construct Validity in Large Language Model Benchmarks
alceballosa  authored a paper 30 days ago
Robust automatic brain vessel segmentation in 3D CTA scans using dynamic 4D-CTA data
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alvarobartt 
posted an update 1 day ago
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2270
Learn how to deploy Microsoft Research VibeVoice ASR on Microsoft Azure Foundry with Hugging Face to generate rich audio transcriptions with Who, When, and What! 💥

> 🕒 60-minute single-pass processing, no chunking or stitching
> 👤 Customized hotwords to guide recognition on domain-specific content
> 📝 Rich transcription: joint ASR + diarization + timestamping in one pass
> 🌍 50+ languages with automatic detection and code-switching support
> 🤗 Deployed on Microsoft Foundry via an OpenAI-compatible Chat Completions API

https://huggingface.co/docs/microsoft-azure/foundry/examples/deploy-vibevoice-asr
mariagrandury 
authored 2 papers 15 days ago
alceballosa 
authored a paper 30 days ago
juanjucm 
posted an update about 1 month ago
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271
Last week,
zai-org dropped zai-org/GLM-4.7-Flash. Now, we bring it to Microsoft Foundry!

- 🏆 30B-A3B MoE, the strongest model in the 30B class. It excels at coding tasks, agentic workflows and reasoning.
- 🤏🏻 Lighter version of his 358B big brother, balancing performance and efficiency.

Not light enough for you? We are also adding
unsloth unsloth/GLM-4.7-Flash-GGUF to the catalog, with GPU and CPU support powered by llama.cpp 🔥

Go join the hype and deploy them from the Hugging Face collection on Microsoft Foundry!
  • 2 replies
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alvarobartt 
posted an update about 1 month ago
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3121
💥 hf-mem v0.4.1 now also estimates KV cache memory requirements for any context length and batch size with the --experimental flag!

uvx hf-mem --model-id ... --experimental will automatically pull the required information from the Hugging Face Hub to include the KV cache estimation, when applicable.

💡 Alternatively, you can also set the --max-model-len, --batch-size and --kv-cache-dtype arguments (à la vLLM) manually if preferred.
  • 1 reply
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davidquicast 
posted an update 3 months ago
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4249
Check out your 2025 Hugging Face Wrapped, a small experimental recap
hf-wrapped/2025
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osanseviero 
authored a paper 5 months ago
mariagrandury 
authored 4 papers 6 months ago
davidquicast 
posted an update 7 months ago
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2887
Just applied for HF Community Grant for “Hugging Research” — a lightweight CodeAgent‑based research assistant built on Hugging Face’s Open Deep Research project for the Hugging Face Hub (models, datasets, Spaces, users, collections, papers). It gathers links via dedicated tools and organizes them for easy review.

As this is for the community, comments and suggestions are appreciated: https://huggingface.co/spaces/daqc/hugging-research/discussions/1#68a94d9bcb035c54bc671119
mariagrandury 
authored 2 papers 9 months ago
Teemu 
posted an update 10 months ago
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939
Aspects of consciousness by Murray Shanahan:

- Awareness of the world (Perception)
- Self-awareness (own body, where it is in the space)
- Imagination / Stream of Consciousness (William James)
- Metacognition (Ability to think what we know)
- Emotions (Feel/Suffer, Sentient)

Source:
https://www.youtube.com/watch?v=v1Py_hWcmkU
osanseviero 
authored a paper 11 months ago
alvarobartt 
posted an update about 1 year ago
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3639
🔥 Agents can do anything! @microsoft Research just announced the release of Magma 8B!

Magma is a new Visual Language Model (VLM) with 8B parameters for multi-modal agents designed to handle complex interactions across virtual and real environments; and it's MIT licensed!

Magma comes with exciting new features such as:
- Introduces the Set-of-Mark and Trace-of-Mark techniques for fine-tuning
- Leverages a large amount of unlabeled video data to learn the spatial-temporal grounding and planning
- A strong generalization and ability to be fine-tuned for other agentic tasks
- SOTA in different multi-modal benchmarks spanning across UI navigation, robotics manipulation, image / video understanding and spatial understanding and reasoning
- Generates goal-driven visual plans and actions for agentic use cases

Model: microsoft/Magma-8B
Technical Report: Magma: A Foundation Model for Multimodal AI Agents (2502.13130)
mariagrandury 
authored a paper over 1 year ago
alvarobartt 
posted an update over 1 year ago
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3039
🤗 Serving Meta Llama 3.1 405B on Google Cloud is now possible via the Hugging Face Deep Learning Containers (DLCs) for Text Generation Inference (TGI)

In this post, we showcase how to deploy https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct-FP8 on an A3 instance with 8 x H100 GPUs on Vertex AI

Thanks to the Hugging Face DLCs for TGI and Google Cloud Vertex AI, deploying a high-performance text generation container for serving Large Language Models (LLMs) has never been easier. And we’re not going to stop here – stay tuned as we enable more experiences to build AI with open models on Google Cloud!

Read the full post at https://huggingface.co/blog/llama31-on-vertex-ai