Post
3429
Should we assemble affordable open-source robots at Hugging Face for the community. Would you buy them? At what price?
- 8 replies
Open-Source AI Meetup
community
AI & ML interests
Open science and open source
SFEvent's activity
Post
2354
Nice new space to see how fast your personal or organization followers are growing on HF:
julien-c/follow-history
As you can see, I still have more followers than @julien-c even if he's trying to change this by building such cool spaces 😝😝😝
julien-c/follow-history
As you can see, I still have more followers than @julien-c even if he's trying to change this by building such cool spaces 😝😝😝
Post
4548
We just crossed 1,500,000 public models on Hugging Face (and 500k spaces, 330k datasets, 50k papers). One new repository is created every 15 seconds. Congratulations all!
- 3 replies
BrigitteTousi
posted
an
update
13 days ago
Post
3280
LeRobot goes to driving school! 🚗🚗🚗
Hugging Face just announced a new collab with Yaak to bring the largest open-source self-driving dataset to LeRobot!
Major kudos to HF's @cadene , as well as @sandhawalia , @Shnissen and the Yaak team!
Check out the blog post here: https://huggingface.co/blog/lerobot-goes-to-driving-school
Hugging Face just announced a new collab with Yaak to bring the largest open-source self-driving dataset to LeRobot!
Major kudos to HF's @cadene , as well as @sandhawalia , @Shnissen and the Yaak team!
Check out the blog post here: https://huggingface.co/blog/lerobot-goes-to-driving-school
-
- 1 reply
BrigitteTousi
posted
an
update
14 days ago
Post
3683
Regardless of X being down or not, so glad I can rely on HF Posts for AI news ❤️🤗
- 1 reply
Post
7225
I was chatting with
@peakji
, one of the cofounders of Manu AI, who told me he was on Hugging Face (very cool!).
He shared an interesting insight which is that agentic capabilities might be more of an alignment problem rather than a foundational capability issue. Similar to the difference between GPT-3 and InstructGPT, some open-source foundation models are simply trained to 'answer everything in one response regardless of the complexity of the question' - after all, that's the user preference in chatbot use cases. Just a bit of post-training on agentic trajectories can make an immediate and dramatic difference.
As a thank you to the community, he shared 100 invite code first-come first serve, just use “HUGGINGFACE” to get access!
He shared an interesting insight which is that agentic capabilities might be more of an alignment problem rather than a foundational capability issue. Similar to the difference between GPT-3 and InstructGPT, some open-source foundation models are simply trained to 'answer everything in one response regardless of the complexity of the question' - after all, that's the user preference in chatbot use cases. Just a bit of post-training on agentic trajectories can make an immediate and dramatic difference.
As a thank you to the community, he shared 100 invite code first-come first serve, just use “HUGGINGFACE” to get access!
- 6 replies
Post
4669
10,000+ models based on Deepseek R1 have been publicly shared on Hugging Face! Which ones are your favorite ones: https://huggingface.co/models?sort=trending&search=r1. Truly game-changer!
Post
5899
Super happy to welcome Nvidia as our latest enterprise hub customer. They have almost 2,000 team members using Hugging Face, and close to 20,000 followers of their org. Can't wait to see what they'll open-source for all of us in the coming months!
Nvidia's org: https://huggingface.co/nvidia
Enterprise hub: https://huggingface.co/enterprise
Nvidia's org: https://huggingface.co/nvidia
Enterprise hub: https://huggingface.co/enterprise
ehristoforu
posted
an
update
28 days ago
Post
2832
Introducing our first standalone model – FluentlyLM Prinum
Introducing the first standalone model from Project Fluently LM! We worked on it for several months, used different approaches and eventually found the optimal one.
General characteristics:
- Model type: Causal language models (QwenForCausalLM, LM Transformer)
- Number of parameters: 32.5B
- Number of parameters (not embedded): 31.0B
- Number of layers: 64
- Context: 131,072 tokens
- Language(s) (NLP): English, French, Spanish, Russian, Chinese, Japanese, Persian (officially supported)
- License: MIT
Creation strategy:
The basis of the strategy is shown in Pic. 2.
We used Axolotl & Unsloth for SFT-finetuning with PEFT LoRA (rank=64, alpha=64) and Mergekit for SLERP and TIES mergers.
Evolution:
🏆 12th place in the Open LLM Leaderboard ( open-llm-leaderboard/open_llm_leaderboard) (21.02.2025)
Detailed results and comparisons are presented in Pic. 3.
Links:
- Model: fluently-lm/FluentlyLM-Prinum
- GGUF version: mradermacher/FluentlyLM-Prinum-GGUF
- Demo on ZeroGPU: ehristoforu/FluentlyLM-Prinum-demo
Introducing the first standalone model from Project Fluently LM! We worked on it for several months, used different approaches and eventually found the optimal one.
General characteristics:
- Model type: Causal language models (QwenForCausalLM, LM Transformer)
- Number of parameters: 32.5B
- Number of parameters (not embedded): 31.0B
- Number of layers: 64
- Context: 131,072 tokens
- Language(s) (NLP): English, French, Spanish, Russian, Chinese, Japanese, Persian (officially supported)
- License: MIT
Creation strategy:
The basis of the strategy is shown in Pic. 2.
We used Axolotl & Unsloth for SFT-finetuning with PEFT LoRA (rank=64, alpha=64) and Mergekit for SLERP and TIES mergers.
Evolution:
🏆 12th place in the Open LLM Leaderboard ( open-llm-leaderboard/open_llm_leaderboard) (21.02.2025)
Detailed results and comparisons are presented in Pic. 3.
Links:
- Model: fluently-lm/FluentlyLM-Prinum
- GGUF version: mradermacher/FluentlyLM-Prinum-GGUF
- Demo on ZeroGPU: ehristoforu/FluentlyLM-Prinum-demo
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-
- 7 replies
Post
2829
What are the best organizations to follow on
@huggingface
?
On top of my head:
- Deepseek (35,000 followers): https://huggingface.co/deepseek-ai
- Meta Llama (27,000 followers): https://huggingface.co/meta-llama
- Black Forrest Labs (11,000 followers): https://huggingface.co/black-forest-labs
- OpenAI (5,000 followers): https://huggingface.co/openai
- Nvidia (16,000 followers): https://huggingface.co/nvidia
- MIcrosoft (9,000 followers): https://huggingface.co/microsoft
- AllenAI (2,000 followers): https://huggingface.co/allenai
- Mistral (5,000 followers): https://huggingface.co/mistralai
- XAI (600 followers): https://huggingface.co/xai-org
- Stability AI (16,000 followers): https://huggingface.co/stabilityai
- Qwen (16,000 followers): https://huggingface.co/Qwen
- GoogleAI (8,000 followers): https://huggingface.co/google
- Unsloth (3,000 followers): https://huggingface.co/unsloth
- Bria AI (4,000 followers): https://huggingface.co/briaai
- NousResearch (1,300 followers): https://huggingface.co/NousResearch
Bonus, the agent course org with 17,000 followers: https://huggingface.co/agents-course
On top of my head:
- Deepseek (35,000 followers): https://huggingface.co/deepseek-ai
- Meta Llama (27,000 followers): https://huggingface.co/meta-llama
- Black Forrest Labs (11,000 followers): https://huggingface.co/black-forest-labs
- OpenAI (5,000 followers): https://huggingface.co/openai
- Nvidia (16,000 followers): https://huggingface.co/nvidia
- MIcrosoft (9,000 followers): https://huggingface.co/microsoft
- AllenAI (2,000 followers): https://huggingface.co/allenai
- Mistral (5,000 followers): https://huggingface.co/mistralai
- XAI (600 followers): https://huggingface.co/xai-org
- Stability AI (16,000 followers): https://huggingface.co/stabilityai
- Qwen (16,000 followers): https://huggingface.co/Qwen
- GoogleAI (8,000 followers): https://huggingface.co/google
- Unsloth (3,000 followers): https://huggingface.co/unsloth
- Bria AI (4,000 followers): https://huggingface.co/briaai
- NousResearch (1,300 followers): https://huggingface.co/NousResearch
Bonus, the agent course org with 17,000 followers: https://huggingface.co/agents-course
- 1 reply
Post
3488
We crossed 1B+ tokens routed to inference providers partners on HF, that we released just a few days ago.
Just getting started of course but early users seem to like it & always happy to be able to partner with cool startups in the ecosystem.
Have you been using any integration and how can we make it better?
https://huggingface.co/blog/inference-providers
Just getting started of course but early users seem to like it & always happy to be able to partner with cool startups in the ecosystem.
Have you been using any integration and how can we make it better?
https://huggingface.co/blog/inference-providers
Post
7238
AI is not a zero-sum game. Open-source AI is the tide that lifts all boats!
BrigitteTousi
posted
an
update
2 months ago
Post
1324
Community fine-tuned models are more carbon efficient than the models they are derived from! 🥳🌿
@alozowski @clefourrier @SaylorTwift @albertvillanova evaluated CO₂ emissions associated with model inference for over 3000 models on the Open LLM Leaderboard. Interesting trends and new insights emerged...👀
Blog Post: https://huggingface.co/blog/leaderboard-emissions-analysis
Leaderboard: open-llm-leaderboard/open_llm_leaderboard
@alozowski @clefourrier @SaylorTwift @albertvillanova evaluated CO₂ emissions associated with model inference for over 3000 models on the Open LLM Leaderboard. Interesting trends and new insights emerged...👀
Blog Post: https://huggingface.co/blog/leaderboard-emissions-analysis
Leaderboard: open-llm-leaderboard/open_llm_leaderboard
Post
4371
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)
-
- 2 replies
ehristoforu
posted
an
update
3 months ago
Post
3688
✒️ Ultraset - all-in-one dataset for SFT training in Alpaca format.
fluently-sets/ultraset
❓ Ultraset is a comprehensive dataset for training Large Language Models (LLMs) using the SFT (instruction-based Fine-Tuning) method. This dataset consists of over 785 thousand entries in eight languages, including English, Russian, French, Italian, Spanish, German, Chinese, and Korean.
🤯 Ultraset solves the problem faced by users when selecting an appropriate dataset for LLM training. It combines various types of data required to enhance the model's skills in areas such as text writing and editing, mathematics, coding, biology, medicine, finance, and multilingualism.
🤗 For effective use of the dataset, it is recommended to utilize only the "instruction," "input," and "output" columns and train the model for 1-3 epochs. The dataset does not include DPO or Instruct data, making it suitable for training various types of LLM models.
❇️ Ultraset is an excellent tool to improve your language model's skills in diverse knowledge areas.
fluently-sets/ultraset
❓ Ultraset is a comprehensive dataset for training Large Language Models (LLMs) using the SFT (instruction-based Fine-Tuning) method. This dataset consists of over 785 thousand entries in eight languages, including English, Russian, French, Italian, Spanish, German, Chinese, and Korean.
🤯 Ultraset solves the problem faced by users when selecting an appropriate dataset for LLM training. It combines various types of data required to enhance the model's skills in areas such as text writing and editing, mathematics, coding, biology, medicine, finance, and multilingualism.
🤗 For effective use of the dataset, it is recommended to utilize only the "instruction," "input," and "output" columns and train the model for 1-3 epochs. The dataset does not include DPO or Instruct data, making it suitable for training various types of LLM models.
❇️ Ultraset is an excellent tool to improve your language model's skills in diverse knowledge areas.
Post
2071
Coming back to Paris Friday to open our new Hugging Face office!
We're at capacity for the party but add your name in the waiting list as we're trying to privatize the passage du Caire for extra space for robots 🤖🦾🦿
https://t.co/enkFXjWndJ
We're at capacity for the party but add your name in the waiting list as we're trying to privatize the passage du Caire for extra space for robots 🤖🦾🦿
https://t.co/enkFXjWndJ
- 1 reply
Vishnou
authored
a
paper
4 months ago
Post
4687
Six predictions for AI in 2025 (and a review of how my 2024 predictions turned out):
- There will be the first major public protest related to AI
- A big company will see its market cap divided by two or more because of AI
- At least 100,000 personal AI robots will be pre-ordered
- China will start to lead the AI race (as a consequence of leading the open-source AI race).
- There will be big breakthroughs in AI for biology and chemistry.
- We will begin to see the economic and employment growth potential of AI, with 15M AI builders on Hugging Face.
How my predictions for 2024 turned out:
- A hyped AI company will go bankrupt or get acquired for a ridiculously low price
✅ (Inflexion, AdeptAI,...)
- Open-source LLMs will reach the level of the best closed-source LLMs
✅ with QwQ and dozens of others
- Big breakthroughs in AI for video, time-series, biology and chemistry
✅ for video 🔴for time-series, biology and chemistry
- We will talk much more about the cost (monetary and environmental) of AI
✅Monetary 🔴Environmental (😢)
- A popular media will be mostly AI-generated
✅ with NotebookLM by Google
- 10 millions AI builders on Hugging Face leading to no increase of unemployment
🔜currently 7M of AI builders on Hugging Face
- There will be the first major public protest related to AI
- A big company will see its market cap divided by two or more because of AI
- At least 100,000 personal AI robots will be pre-ordered
- China will start to lead the AI race (as a consequence of leading the open-source AI race).
- There will be big breakthroughs in AI for biology and chemistry.
- We will begin to see the economic and employment growth potential of AI, with 15M AI builders on Hugging Face.
How my predictions for 2024 turned out:
- A hyped AI company will go bankrupt or get acquired for a ridiculously low price
✅ (Inflexion, AdeptAI,...)
- Open-source LLMs will reach the level of the best closed-source LLMs
✅ with QwQ and dozens of others
- Big breakthroughs in AI for video, time-series, biology and chemistry
✅ for video 🔴for time-series, biology and chemistry
- We will talk much more about the cost (monetary and environmental) of AI
✅Monetary 🔴Environmental (😢)
- A popular media will be mostly AI-generated
✅ with NotebookLM by Google
- 10 millions AI builders on Hugging Face leading to no increase of unemployment
🔜currently 7M of AI builders on Hugging Face
- 4 replies
Post
4439
Hugging Face is becoming the best place to share the most viral AI apps with spaces.
Kolors Virtual Try-on just crossed 6,000,000 unique visitors & is now the #5 most popular space. Congrats to the Kwai Kolors team!
Kwai-Kolors/Kolors-Virtual-Try-On
Kolors Virtual Try-on just crossed 6,000,000 unique visitors & is now the #5 most popular space. Congrats to the Kwai Kolors team!
Kwai-Kolors/Kolors-Virtual-Try-On
- 2 replies