You can just ask things 🗣️ "show me messages in the coding category that are in the top 10% of reward model scores" Download really high quality instructions from the Argilla Llama3.1 405B synthetic dataset 🔥
Most liked and most downloaded open-source AI models from 2022 to 2024 Interactive viz: aiworld.eu/embed/model/... Discussion: huggingface.co/spaces/huggi...
The amazing, new Qwen2.5-Coder 32B model can now write SQL for any @hf.co dataset ✨
This is insane! Structured generation in the browser with the new @hf.co SmolLM2-1.7B model • Tiny 1.7B LLM running at 88 tokens / second ⚡ • Powered by MLC/WebLLM on WebGPU 🔥 • JSON Structured Generation entirely in the browser 🤏
Releasing SmolVLM, a small 2 billion parameters Vision+Language Model (VLM) built for on-device/in-browser inference with images/videos. Outperforms all models at similar GPU RAM usage and tokens throughputs Blog post: huggingface.co/blog/smolvlm
The OpenLLM Leaderboard just passed 2k evals 🥳 Here's a look at the distribution of average scores for all those models! Great work by the @huggingface.bsky.social team to do these evals!
Automatically tracking all Ollama requests to a dataset with the new observers python library! With just a few lines of code all your requests can be sent to @huggingface.bsky.social datasets for annotating, analysis and observability 🔭
observers 🔭 - automatically log all OpenAI compatible requests to a dataset 💽 • supports any OpenAI compatible endpoint 💪 • supports @duckdb.org, @huggingface.bsky.social datasets and Argilla as stores > pip install observers
SmolTalk is out 🗣️ Over 1M high quality instructions used for training SmolLM2, one of the best small language models in the industry. huggingface.co/datasets/Hug...
HuggingFaceTB/smoltalk · Datasets at Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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Observers: A Lightweight SDK for AI Observability TLDR; - Track and record interactions with AI models - Store observations in multiple backends @huggingface.bsky.social, @duckdb.org or Argilla - Query and analyse your AI interactions with ease GitHub: github.com/cfahlgren1/o...
Foursquare just open sourced their 100 million place point of interest dataset! Some notes on poking around with it using DuckDB (it's Parquet files on S3) simonwillison.net/2024/Nov/20/...
Foursquare Open Source Places: A new foundational dataset for the geospatial community
I did not expect this! > [...] we are announcing today the general availability of a foundational open data set, Foursquare Open Source Places ("FSQ OS Places"). This base layer …
simonwillison.net
Range requests + Parquet is what makes the Hugging Face SQL Console possible to query datasets entirely in the browser
Simon Willison@simonwillison.net · 2y agoHTTP range requests are one of those interesting technologies that have almost universal support without most people even being aware of them - because you can't do streaming video formats with the ability to skip ahead without them
duckdb-gsheets v0.0.3 is out, courtesy of @a13x.bsky.social the power is terrifying! duckdb-gsheets.com
When XetHub joined Hugging Face, we brainstormed how to share our tech with the community. The magic? Versioning chunks, not files, giving rise to: 🧠 Smarter storage ⏩ Faster uploads 🚀 Efficient downloads Curious? Read the blog and let us know how it could help your workflows!
From Files to Chunks: Improving HF Storage Efficiency
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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