Insights from the ICLR Peer Review and Rebuttal Process
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Card forensics using VLM localized prompt approach
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Post
1217
New post is live!
This time we cover some major updates to
🤗
This time we cover some major updates to
transformers.🤗
-
- 1 reply
burtenshaw
posted
an
update
3 months ago
Post
5508
Smol course has a distinctive approach to teaching post-training, so I'm posting about how it’s different to other post-training courses, including the llm course that’s already available.
In short, the smol course is just more direct that any of the other course, and intended for semi-pro post trainers.
- It’s a minimal set of instructions on the core parts.
- It’s intended to bootstrap real projects you're working on.
- The material handsover to existing documentation for details
- Likewise, it handsover to the LLM course for basics.
- Assessment is based on a leaderboard, without reading all the material.
To start the smol course, follow here:
smol-course
In short, the smol course is just more direct that any of the other course, and intended for semi-pro post trainers.
- It’s a minimal set of instructions on the core parts.
- It’s intended to bootstrap real projects you're working on.
- The material handsover to existing documentation for details
- Likewise, it handsover to the LLM course for basics.
- Assessment is based on a leaderboard, without reading all the material.
To start the smol course, follow here:
smol-course
Post
3101
🚀 Ever dreamed of training your own Large Language Model from scratch? What if I told you it doesn't require a supercomputer or PhD in ML? 🤯
Introducing LLM Trainer - the educational framework that makes LLM training accessible to EVERYONE! Whether you're on a CPU-only laptop or scaling to distributed GPUs, we've got you covered. 💻➡️🖥️
Why LLM Trainer? Because existing tools are either too simplistic (hiding the magic) or too complex (requiring expert knowledge). We bridge the gap with:
🎓 Educational transparency - every component built from scratch with clear code
💻 CPU-first approach - start training immediately, no GPU needed
🔧 Full customization - modify anything you want
📈 Seamless scaling - from laptop to cluster without code changes
🤝 HuggingFace integration - works with existing models & tokenizers
Key highlights:
✅ Built-in tokenizers (BPE, WordPiece, HF wrappers)
✅ Complete Transformer implementation from scratch
✅ Optimized for CPU training
✅ Advanced features: mixed precision, gradient checkpointing, multiple generation strategies
✅ Comprehensive monitoring & metrics
Perfect for:
- Students learning transformers
- Researchers prototyping new ideas
- Developers building domain-specific models
Ready to train your first LLM? It's easier than you think!
🔗 Check it out: https://github.com/HelpingAI/llm-trainer
📚 Docs: Getting Started Guide
💬 Join the community: GitHub Discussions
#AI #MachineLearning #LLM #DeepLearning #OpenSource #Python #HuggingFace #NLP
Special thanks to HuggingFace and PyTorch teams for the amazing ecosystem! 🙏
Introducing LLM Trainer - the educational framework that makes LLM training accessible to EVERYONE! Whether you're on a CPU-only laptop or scaling to distributed GPUs, we've got you covered. 💻➡️🖥️
Why LLM Trainer? Because existing tools are either too simplistic (hiding the magic) or too complex (requiring expert knowledge). We bridge the gap with:
🎓 Educational transparency - every component built from scratch with clear code
💻 CPU-first approach - start training immediately, no GPU needed
🔧 Full customization - modify anything you want
📈 Seamless scaling - from laptop to cluster without code changes
🤝 HuggingFace integration - works with existing models & tokenizers
Key highlights:
✅ Built-in tokenizers (BPE, WordPiece, HF wrappers)
✅ Complete Transformer implementation from scratch
✅ Optimized for CPU training
✅ Advanced features: mixed precision, gradient checkpointing, multiple generation strategies
✅ Comprehensive monitoring & metrics
Perfect for:
- Students learning transformers
- Researchers prototyping new ideas
- Developers building domain-specific models
Ready to train your first LLM? It's easier than you think!
🔗 Check it out: https://github.com/HelpingAI/llm-trainer
📚 Docs: Getting Started Guide
💬 Join the community: GitHub Discussions
#AI #MachineLearning #LLM #DeepLearning #OpenSource #Python #HuggingFace #NLP
Special thanks to HuggingFace and PyTorch teams for the amazing ecosystem! 🙏
- 1 reply
burtenshaw
posted
an
update
3 months ago
Post
5393
new smol course
If you’re building with or learning about post training AI models right now, we have a new FREE and CERTIFIED course.
🔗 Follow the org to join in
smol-course
The course builds on smol course v1 which was the fastest way to learn to train your custom AI models. It now has:
- A leaderboard for students to submit models to
- Certification based on exams and leaderboards
- Prizes based on Leaderboards
- Up to date content on TRL and SmolLM3
- Deep integration with the Hub’s compute for model training and evaluation
We will release chapters every few weeks, so you can follow the org to stay updated.
If you’re building with or learning about post training AI models right now, we have a new FREE and CERTIFIED course.
🔗 Follow the org to join in
smol-course
The course builds on smol course v1 which was the fastest way to learn to train your custom AI models. It now has:
- A leaderboard for students to submit models to
- Certification based on exams and leaderboards
- Prizes based on Leaderboards
- Up to date content on TRL and SmolLM3
- Deep integration with the Hub’s compute for model training and evaluation
We will release chapters every few weeks, so you can follow the org to stay updated.
- 2 replies
burtenshaw
posted
an
update
3 months ago
Post
3014
The open source AI community is just made of people who are passionate and care about their work. So we thought it would be cool to share our favourite icons of the community with a fun award.
Winners get free Hugging Face Pro Subscriptions, Merchandise, or compute credits for the hub.
🔗 Follow and nominate here:
community-spotlight
This is a new initiative to recognise and celebrate the incredible work being done by community members. It's all about inspiring more collaboration and innovation in the world of machine learning and AI.
They're highlighting contributors in four key areas:
- model creators: building and sharing innovative and state-of-the-art models.
- educators: sharing knowledge through posts, articles, demos, and events.
- tool builders: creating the libraries, frameworks, and applications that we all use.
- community champions: supporting and mentoring others in forums.
Know someone who deserves recognition? Nominate them by opening a post in the Hugging Face community forum.
Winners get free Hugging Face Pro Subscriptions, Merchandise, or compute credits for the hub.
🔗 Follow and nominate here:
community-spotlight
This is a new initiative to recognise and celebrate the incredible work being done by community members. It's all about inspiring more collaboration and innovation in the world of machine learning and AI.
They're highlighting contributors in four key areas:
- model creators: building and sharing innovative and state-of-the-art models.
- educators: sharing knowledge through posts, articles, demos, and events.
- tool builders: creating the libraries, frameworks, and applications that we all use.
- community champions: supporting and mentoring others in forums.
Know someone who deserves recognition? Nominate them by opening a post in the Hugging Face community forum.
- 1 reply
[Support] Community Articles
🚀
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1
86
#5 opened over 1 year ago
by
victor
DandinPower
authored
2
papers
4 months ago
Post
4133
🚀 Dhanishtha-2.0-preview-0825 Is Here
The Intermediate Thinking Model just leveled up again.
With sharper reasoning, better tool use, and expanded capabilities, Dhanishtha-2.0-preview-0825 is now live and ready to impress.
🧠 What Makes Dhanishtha Special?
Unlike typical CoT models that only thinks one time, Dhanishtha thinks iteratively:
> Think → Answer → Rethink → Improve → Rethink again if needed.
🔗 Try it now: HelpingAI/Dhanishtha-2.0-preview-0825
🔞 Dhanishtha NSFW Preview
For those exploring more expressive and immersive roleplay scenarios, we’re also releasing:
HelpingAI/Dhanishtha-nsfw
A specialized version tuned for adult-themed interactions and character-driven roleplay.
🔗 Explore it here: HelpingAI/Dhanishtha-nsfw
💬 You can also try all of these live at chat.helpingai.co
The Intermediate Thinking Model just leveled up again.
With sharper reasoning, better tool use, and expanded capabilities, Dhanishtha-2.0-preview-0825 is now live and ready to impress.
🧠 What Makes Dhanishtha Special?
Unlike typical CoT models that only thinks one time, Dhanishtha thinks iteratively:
> Think → Answer → Rethink → Improve → Rethink again if needed.
🔗 Try it now: HelpingAI/Dhanishtha-2.0-preview-0825
🔞 Dhanishtha NSFW Preview
For those exploring more expressive and immersive roleplay scenarios, we’re also releasing:
HelpingAI/Dhanishtha-nsfw
A specialized version tuned for adult-themed interactions and character-driven roleplay.
🔗 Explore it here: HelpingAI/Dhanishtha-nsfw
💬 You can also try all of these live at chat.helpingai.co
- 4 replies
Post
3761
We've crossed 1 million repositories backed by Xet storage on Hugging Face! 🚀🚀🚀
You can follow along our progress converting the Hub from Git LFS to Xet at jsulz/ready-xet-go
We have a lot of repos left to migrate, which means I have plenty of time to add more animations 🤪
You can follow along our progress converting the Hub from Git LFS to Xet at jsulz/ready-xet-go
We have a lot of repos left to migrate, which means I have plenty of time to add more animations 🤪
Post
877
I have always advocated for writing techinical stories without using LLMs.
The following one page editorial really drives the point home.
https://www.nature.com/articles/s44222-025-00323-4
The following one page editorial really drives the point home.
https://www.nature.com/articles/s44222-025-00323-4
Post
3158
🎉 Dhanishtha-2.0-preview-0725 is Now Live
The Intermediate Thinking Model just got even better.
With the new update, Dhanishtha is now sharper, smarter, and trained further on tool use
🧠 What Makes Dhanishtha Different?
Unlike standard COT models that give one-shot responses, Dhanishtha thinks in layers:
> Think → Answer → Rethink → Improve → Rethink again if needed.
HelpingAI/Dhanishtha-2.0-preview-0725
The Intermediate Thinking Model just got even better.
With the new update, Dhanishtha is now sharper, smarter, and trained further on tool use
🧠 What Makes Dhanishtha Different?
Unlike standard COT models that give one-shot responses, Dhanishtha thinks in layers:
> Think → Answer → Rethink → Improve → Rethink again if needed.
HelpingAI/Dhanishtha-2.0-preview-0725