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
4 minutes ago
cfahlgren1/react-code-instructions
updated
a dataset
about 5 hours ago
cfahlgren1/hub-stats
updated
a dataset
about 5 hours ago
cfahlgren1/hub-stats
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cfahlgren1's activity
posted
an
update
about 12 hours ago
Post
343
You'll notice the AI in the SQL Console is much better at working with chatml conversations:
Here's example of unnesting the cfahlgren1/react-code-instructions in less than 10 seconds by asking it. Check it out here: cfahlgren1/react-code-instructions
- "show me the average assistant response length"
- "extract user, system, and assistant messages into separate columns"
It's super easy to work with conversational datasets now with natural language 🗣️
Here's example of unnesting the cfahlgren1/react-code-instructions in less than 10 seconds by asking it. Check it out here: cfahlgren1/react-code-instructions
- "show me the average assistant response length"
- "extract user, system, and assistant messages into separate columns"
It's super easy to work with conversational datasets now with natural language 🗣️
reacted to
clem's
post with 🚀🤗❤️
about 12 hours ago
Post
1195
Cool to see
@ylecun
joining the top 10 of most followed on HF!
(and leaderboard by @mvaloatto is here: mvaloatto/TCTF)
(and leaderboard by @mvaloatto is here: mvaloatto/TCTF)
- 1 reply
posted
an
update
5 days ago
Post
2967
The
deepseek-ai/DeepSeek-V3 is very good! I have been playing with it and found it is really good at one-shotting a pretty good landing page.
You can play with it here: https://deepseek-artifacts.vercel.app
All the responses get saved in the cfahlgren1/react-code-instructions dataset. Hopefully we can build one of the biggest, highest quality frontend datasets on the hub 💪
You can play with it here: https://deepseek-artifacts.vercel.app
All the responses get saved in the cfahlgren1/react-code-instructions dataset. Hopefully we can build one of the biggest, highest quality frontend datasets on the hub 💪
reacted to
davidberenstein1957's
post with 🧠👀
5 days ago
Post
1840
Fine-tuning ModernBERT for text classification using synthetic data generation
From prompt to model in 3 steps.
1 dataset description
20 minutes of generating
60 minutes of fine-tuning on my Macbook Pro
Tutorial: https://nbsanity.com/static/552eb50cbd91bedb4e5b73fddca2664a/fine-tune-modernbert-classifier.html
From prompt to model in 3 steps.
1 dataset description
20 minutes of generating
60 minutes of fine-tuning on my Macbook Pro
Tutorial: https://nbsanity.com/static/552eb50cbd91bedb4e5b73fddca2664a/fine-tune-modernbert-classifier.html
reacted to
lorraine2's
post with 🚀
18 days ago
Post
1988
🦙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 👍🤗❤️🔥
24 days ago
Post
7926
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
about 1 month ago
Post
1926
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
about 1 month ago
Post
3011
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
916
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 2 months ago
or shakespeare 🤣 @not-lain
posted
an
update
about 2 months ago
Post
874
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 2 months ago
Post
1310
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 2 months ago
Heavy is the head that wears the crown
reacted to
fracapuano's
post with ❤️
about 2 months ago
Post
1026
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🦾