Introducing Observers: AI Observability with Hugging Face datasets through a lightweight SDK
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Caleb Fahlgren PRO
cfahlgren1
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updated
a dataset
about 3 hours ago
cfahlgren1/hub-stats
liked
a model
about 5 hours ago
deepseek-ai/DeepSeek-V3-Base
new activity
2 days ago
cfahlgren1/sql-snippets:Request for a new snippet:
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cfahlgren1's activity
reacted to
lorraine2's
post with 🚀
9 days ago
Post
1966
🦙New NVIDIA paper: LLaMA-Mesh 🦙
We enable large language models to generate and understand 3D meshes by representing them as text and fine-tuning. This unifies the 3D and text modalities in a single model and preserves language abilities, unlocking conversational 3D creation with mesh understanding.
🔎 Project Page: https://research.nvidia.com/labs/toronto-ai/LLaMA-Mesh/
🕹️ Interactive Demo: Zhengyi/LLaMA-Mesh (courtesy of HuggingFace and Gradio)
📖 Full Paper: https://arxiv.org/abs/2411.09595
👨💻Code: https://github.com/nv-tlabs/LLaMa-Mesh
💾 Model Checkpoint: Zhengyi/LLaMA-Mesh
🧩 Blender Addon: https://github.com/huggingface/meshgen (courtesy of Dylan Ebert)
🎥 5-min Overview Video: https://youtu.be/eZNazN-1lPo?si=-idQa5aaceVw0Bbj (courtesy of AI Papers Academy)
We enable large language models to generate and understand 3D meshes by representing them as text and fine-tuning. This unifies the 3D and text modalities in a single model and preserves language abilities, unlocking conversational 3D creation with mesh understanding.
🔎 Project Page: https://research.nvidia.com/labs/toronto-ai/LLaMA-Mesh/
🕹️ Interactive Demo: Zhengyi/LLaMA-Mesh (courtesy of HuggingFace and Gradio)
📖 Full Paper: https://arxiv.org/abs/2411.09595
👨💻Code: https://github.com/nv-tlabs/LLaMa-Mesh
💾 Model Checkpoint: Zhengyi/LLaMA-Mesh
🧩 Blender Addon: https://github.com/huggingface/meshgen (courtesy of Dylan Ebert)
🎥 5-min Overview Video: https://youtu.be/eZNazN-1lPo?si=-idQa5aaceVw0Bbj (courtesy of AI Papers Academy)
reacted to
julien-c's
post with 👍🤗❤️🔥
15 days ago
Post
7611
After some heated discussion 🔥, we clarify our intent re. storage limits on the Hub
TL;DR:
- public storage is free, and (unless blatant abuse) unlimited. We do ask that you consider upgrading to PRO and/or Enterprise Hub if possible
- private storage is paid above a significant free tier (1TB if you have a paid account, 100GB otherwise)
docs: https://huggingface.co/docs/hub/storage-limits
We optimize our infrastructure continuously to scale our storage for the coming years of growth in Machine learning, to the benefit of the community 🔥
cc: @reach-vb @pierric @victor and the HF team
TL;DR:
- public storage is free, and (unless blatant abuse) unlimited. We do ask that you consider upgrading to PRO and/or Enterprise Hub if possible
- private storage is paid above a significant free tier (1TB if you have a paid account, 100GB otherwise)
docs: https://huggingface.co/docs/hub/storage-limits
We optimize our infrastructure continuously to scale our storage for the coming years of growth in Machine learning, to the benefit of the community 🔥
cc: @reach-vb @pierric @victor and the HF team
- 28 replies
posted
an
update
22 days ago
Post
1810
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 Llama3.1 405B synthetic dataset 🔥
argilla/magpie-ultra-v1.0
"show me messages in the coding category that are in the top 10% of reward model scores"
Download really high quality instructions from the Llama3.1 405B synthetic dataset 🔥
argilla/magpie-ultra-v1.0
posted
an
update
24 days ago
Post
2991
We just dropped an LLM inside the SQL Console 🤯
The amazing, new Qwen/Qwen2.5-Coder-32B-Instruct model can now write SQL for any Hugging Face dataset ✨
It's 2025, you shouldn't be hand writing SQL! This is a big step in making it where anyone can do in depth analysis on a dataset. Let us know what you think 🤗
The amazing, new Qwen/Qwen2.5-Coder-32B-Instruct model can now write SQL for any Hugging Face dataset ✨
It's 2025, you shouldn't be hand writing SQL! This is a big step in making it where anyone can do in depth analysis on a dataset. Let us know what you think 🤗
posted
an
update
about 1 month ago
Post
910
observers 🔭 - automatically log all OpenAI compatible requests to a dataset💽
• supports any OpenAI compatible endpoint 💪
• supports DuckDB, Hugging Face Datasets, and Argilla as stores
> pip install observers
No complex framework. Just a few lines of code to start sending your traces somewhere. Let us know what you think! @davidberenstein1957 and I will continue iterating!
Here's an example dataset that was logged to Hugging Face from Ollama: cfahlgren1/llama-3.1-awesome-chatgpt-prompts
• supports any OpenAI compatible endpoint 💪
• supports DuckDB, Hugging Face Datasets, and Argilla as stores
> pip install observers
No complex framework. Just a few lines of code to start sending your traces somewhere. Let us know what you think! @davidberenstein1957 and I will continue iterating!
Here's an example dataset that was logged to Hugging Face from Ollama: cfahlgren1/llama-3.1-awesome-chatgpt-prompts
replied to
their
post
about 1 month ago
or shakespeare 🤣 @not-lain
posted
an
update
about 1 month ago
Post
870
You can create charts, leaderboards, and filters on top of any Hugging Face dataset in less than a minute
• ASCII Bar Charts 📊
• Powered by DuckDB WASM ⚡
• Download results to Parquet 💽
• Embed and Share results with friends 📬
Do you have any interesting queries?
• ASCII Bar Charts 📊
• Powered by DuckDB WASM ⚡
• Download results to Parquet 💽
• Embed and Share results with friends 📬
Do you have any interesting queries?
reacted to
davanstrien's
post with ❤️
about 1 month ago
Post
1306
huggingface.co/DIBT is dead! Long live https://huggingface.co/data-is-better-together!
We're working on some very cool projects so we're doing a bit of tidying of the Data is Better Together Hub org 🤓
replied to
their
post
about 1 month ago
Heavy is the head that wears the crown
reacted to
fracapuano's
post with ❤️
about 1 month ago
Post
1020
Sharing what we have built over the course of the weekend at the
@llamameta
hackathon, by Cerebral Valley in London 🇬🇧 👇
@gabrycina @calebgcc and I competed with 200+ participants and 50+ teams for a 24-hrs sprint centered around hacking for impact! We focused on applications of robotics to those in need of assisted living, moving our focus to enable greater autonomy and accessibility of robotics in everyday life.
complete list of assets 👇
🤗 trained robotics policies
v1:
- fracapuano/moss-pills
- fracapuano/moss-cup
v2:
- fracapuano/meta-grasp
🤗 datasets
v1:
- fracapuano/pills
- fracapuano/cup
v2:
- fracapuano/cupim
You can find a live demo of our submission at: https://x.com/_fracapuano/status/1858102728691458554
If you want to know more about how we collected 100GB+ of data, trained multiple RL-policies using @lerobot and used Llama-3.2 models to handle user interactions and switch between tasks, go ahead and have a look! Also, don't be a stranger, and reach out 🦾
Our project is fully open-source, for the community (and ourselves, 👨🍳) to build! A huge thank you to @cadene for the help (and the robot 🤭) - truly feeling these hugs-vibes 🤗 , and to @thomwolf and @clem for sharing our work across
Little extra:
➡️ Our 🧠EEG waves🧠-based control of the 🦾robotic arm🦾
@gabrycina @calebgcc and I competed with 200+ participants and 50+ teams for a 24-hrs sprint centered around hacking for impact! We focused on applications of robotics to those in need of assisted living, moving our focus to enable greater autonomy and accessibility of robotics in everyday life.
complete list of assets 👇
🤗 trained robotics policies
v1:
- fracapuano/moss-pills
- fracapuano/moss-cup
v2:
- fracapuano/meta-grasp
🤗 datasets
v1:
- fracapuano/pills
- fracapuano/cup
v2:
- fracapuano/cupim
You can find a live demo of our submission at: https://x.com/_fracapuano/status/1858102728691458554
If you want to know more about how we collected 100GB+ of data, trained multiple RL-policies using @lerobot and used Llama-3.2 models to handle user interactions and switch between tasks, go ahead and have a look! Also, don't be a stranger, and reach out 🦾
Our project is fully open-source, for the community (and ourselves, 👨🍳) to build! A huge thank you to @cadene for the help (and the robot 🤭) - truly feeling these hugs-vibes 🤗 , and to @thomwolf and @clem for sharing our work across
Little extra:
➡️ Our 🧠EEG waves🧠-based control of the 🦾robotic arm🦾
reacted to
LukeNeumann's
post with 🤯
about 1 month ago
Post
1219
Nine years ago, I uploaded the first 8K resolution video to YouTube and I've been stockpiling 8K footage ever since: https://www.youtube.com/watch?v=sLprVF6d7Ug&t
Should @Overlaiapp release the first open-source 8K video dataset?
Could anyone even fine tune a model with this?😅
Should @Overlaiapp release the first open-source 8K video dataset?
Could anyone even fine tune a model with this?😅
-
- 6 replies
replied to
LukeNeumann's
post
about 1 month ago
Would be massive! Let us know if you need any help 🤗
reacted to
dvilasuero's
post with 🚀🤗
about 1 month ago
Post
1106
@Jesse-marqo
and the Marqo team are killing it on the Hub: top embedding models and datasets!
Here's how to start using their new evaluation dataset for curation and labelling:
1. Deploy Argilla on Spaces: https://huggingface.co/new-space?template=argilla%2Fargilla-template-space
2. Load Marqo/amazon-products-eval with the UI wizard.
3. Start curating!
Here's how to start using their new evaluation dataset for curation and labelling:
1. Deploy Argilla on Spaces: https://huggingface.co/new-space?template=argilla%2Fargilla-template-space
2. Load Marqo/amazon-products-eval with the UI wizard.
3. Start curating!
posted
an
update
about 1 month ago
Post
745
What rank are you on Hugging Face Top Yappers? 🗣️
Find your rank here with this link: cfahlgren1/hub-stats
The Top 3:
- @fdaudens
- @singhsidhukuldeep
- @akhaliq
I am at #71 and need to get my numbers up! 📈
Find your rank here with this link: cfahlgren1/hub-stats
The Top 3:
- @fdaudens
- @singhsidhukuldeep
- @akhaliq
I am at #71 and need to get my numbers up! 📈
-
- 4 replies
reacted to
nyuuzyou's
post with 🔥
about 1 month ago
Post
949
🖼️ Introducing Public Domain Pictures Dataset -
nyuuzyou/publicdomainpictures
Dataset highlights:
- 644,412 public domain images with comprehensive metadata from publicdomainpictures.net
- English language metadata including titles, descriptions, and keywords
- Each entry contains rich metadata including:
- Unique image ID and full-size image URLs
- Detailed titles and descriptions
- Keyword/tag collections
- Creator attribution
- Released to the public domain under Creative Commons Zero (CC0) license
Dataset highlights:
- 644,412 public domain images with comprehensive metadata from publicdomainpictures.net
- English language metadata including titles, descriptions, and keywords
- Each entry contains rich metadata including:
- Unique image ID and full-size image URLs
- Detailed titles and descriptions
- Keyword/tag collections
- Creator attribution
- Released to the public domain under Creative Commons Zero (CC0) license
-
- 2 replies
posted
an
update
about 1 month ago
Post
3091
You can clean and format datasets entirely in the browser with a few lines of SQL.
In this post, I replicate the process @mlabonne used to clean the new microsoft/orca-agentinstruct-1M-v1 dataset.
The cleaning process consists of:
- Joining the separate splits together / add split column
- Converting string messages into list of structs
- Removing empty system prompts
https://huggingface.co/blog/cfahlgren1/the-beginners-guide-to-cleaning-a-dataset
Here's his new cleaned dataset: mlabonne/orca-agentinstruct-1M-v1-cleaned
In this post, I replicate the process @mlabonne used to clean the new microsoft/orca-agentinstruct-1M-v1 dataset.
The cleaning process consists of:
- Joining the separate splits together / add split column
- Converting string messages into list of structs
- Removing empty system prompts
https://huggingface.co/blog/cfahlgren1/the-beginners-guide-to-cleaning-a-dataset
Here's his new cleaned dataset: mlabonne/orca-agentinstruct-1M-v1-cleaned
- 1 reply