SmolLM - blazingly fast and remarkably powerful
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Loubna Ben Allal
loubnabnl
AI & ML interests
LLMs, ML for code, Synthetic data
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#18 opened 1 day ago
by
darkmatter2222
darkmatter2222
liked
a
dataset
1 day ago
updated
a
Space
1 day ago
upvoted
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collection
1 day ago
Reacted to
merve's
post with 🔥
1 day ago
Post
2063
Small yet mighty! 💫
We are releasing SmolVLM: a new 2B small vision language made for on-device use, fine-tunable on consumer GPU, immensely memory efficient 🤠
We release three checkpoints under Apache 2.0: SmolVLM-Instruct, SmolVLM-Synthetic and SmolVLM-Base HuggingFaceTB/smolvlm-6740bd584b2dcbf51ecb1f39
Learn more from our blog here: huggingface.co/blog/smolvlm
This release comes with a demo, fine-tuning code, MLX integration and TRL integration for DPO 💝
Try the demo: HuggingFaceTB/SmolVLM
Fine-tuning Recipe: https://github.com/huggingface/smollm/blob/main/finetuning/Smol_VLM_FT.ipynb
Also TRL integration for DPO 💗
We are releasing SmolVLM: a new 2B small vision language made for on-device use, fine-tunable on consumer GPU, immensely memory efficient 🤠
We release three checkpoints under Apache 2.0: SmolVLM-Instruct, SmolVLM-Synthetic and SmolVLM-Base HuggingFaceTB/smolvlm-6740bd584b2dcbf51ecb1f39
Learn more from our blog here: huggingface.co/blog/smolvlm
This release comes with a demo, fine-tuning code, MLX integration and TRL integration for DPO 💝
Try the demo: HuggingFaceTB/SmolVLM
Fine-tuning Recipe: https://github.com/huggingface/smollm/blob/main/finetuning/Smol_VLM_FT.ipynb
Also TRL integration for DPO 💗
updated
a
dataset
1 day ago
Limitation - context length of the BERT classifier?
2
#17 opened 2 days ago
by
liyucheng
liyucheng
Reacted to
thomwolf's
post with 🔥
2 days ago
Post
1461
Interesting long read from
@evanmiller-anthropic
on having a better founded statistical approach to Language Model Evaluations:
https://www.anthropic.com/research/statistical-approach-to-model-evals
Worth a read if you're into LLM evaluations!
Cc @clefourrier
https://www.anthropic.com/research/statistical-approach-to-model-evals
Worth a read if you're into LLM evaluations!
Cc @clefourrier
- 1 reply
liked
a
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2 days ago
Reacted to
openfree's
post with 👀🔥
2 days ago
Post
2832
🤗 HuggingFace Trending TOP 300 Board - Featuring AI Rating System
📊 Service Introduction
A comprehensive dashboard that provides at-a-glance access to the real-time TOP 300 trending Spaces, Models, and Datasets on HuggingFace.
Our specially developed AI rating system evaluates the practical value and growth potential of each item.
⭐ Key Features
1. AI Rising Rate
Growth potential evaluation based on creation date and ranking
5-tier star rating system (★★★★★)
Evaluation Criteria:
Recency: Higher relative weights for recently created items
Ranking Impact: Higher relative weights for top rankings
Comprehensive assessment using statistical/analytical models applied to AI
2. AI Popularity Score
Comprehensive evaluation combining objective popularity and Rising Rate
18-tier grading system from AAA+ to B-
Evaluation Elements:
Base Score: Benchmark based on likes, downloads, comments, etc.
Additional Score: Rising Rate applied as a weighted factor
Comprehensive assessment using statistical/analytical models applied to AI
3. Visualization Features
Real-time screenshot capture with caching
Intuitive card-based UI
Responsive grid layout
Pastel gradient design
🎯 Applications
AI/ML Project Trend Analysis
Early Discovery of Promising Models/Datasets
Community Activity Monitoring
Research/Development Direction Reference
💡 Key Advantages
Real-time TOP 300 ranking
AI-based objective evaluation system
Fast loading with caching system
Intuitive and modern UI/UX
Integrated dashboard for 3 categories
🔄 Update Cycle
Real-time data reflection
Manual refresh option
Minimized server load through screenshot caching
🎁 Future Plans
Addition of detailed analysis report feature
Custom filtering options
Time-series trend analysis
Category-specific detailed statistics
🌐 How to Access
openfree/trending-board
#HuggingFace #AI #MachineLearning #TrendingBoard #DataScience #
📊 Service Introduction
A comprehensive dashboard that provides at-a-glance access to the real-time TOP 300 trending Spaces, Models, and Datasets on HuggingFace.
Our specially developed AI rating system evaluates the practical value and growth potential of each item.
⭐ Key Features
1. AI Rising Rate
Growth potential evaluation based on creation date and ranking
5-tier star rating system (★★★★★)
Evaluation Criteria:
Recency: Higher relative weights for recently created items
Ranking Impact: Higher relative weights for top rankings
Comprehensive assessment using statistical/analytical models applied to AI
2. AI Popularity Score
Comprehensive evaluation combining objective popularity and Rising Rate
18-tier grading system from AAA+ to B-
Evaluation Elements:
Base Score: Benchmark based on likes, downloads, comments, etc.
Additional Score: Rising Rate applied as a weighted factor
Comprehensive assessment using statistical/analytical models applied to AI
3. Visualization Features
Real-time screenshot capture with caching
Intuitive card-based UI
Responsive grid layout
Pastel gradient design
🎯 Applications
AI/ML Project Trend Analysis
Early Discovery of Promising Models/Datasets
Community Activity Monitoring
Research/Development Direction Reference
💡 Key Advantages
Real-time TOP 300 ranking
AI-based objective evaluation system
Fast loading with caching system
Intuitive and modern UI/UX
Integrated dashboard for 3 categories
🔄 Update Cycle
Real-time data reflection
Manual refresh option
Minimized server load through screenshot caching
🎁 Future Plans
Addition of detailed analysis report feature
Custom filtering options
Time-series trend analysis
Category-specific detailed statistics
🌐 How to Access
openfree/trending-board
#HuggingFace #AI #MachineLearning #TrendingBoard #DataScience #
- 3 replies
posted
an
update
3 days ago
Post
1223
Making SmolLM2 reproducible: open-sourcing our training & evaluation toolkit 🛠️ https://github.com/huggingface/smollm/
- Pre-training code with nanotron
- Evaluation suite with lighteval
- Synthetic data generation using distilabel (powers our new SFT dataset HuggingFaceTB/smoltalk)
- Post-training scripts with TRL & the alignment handbook
- On-device tools with llama.cpp for summarization, rewriting & agents
Apache 2.0 licensed. V2 pre-training data mix coming soon!
Which other tools should we add next?
- Pre-training code with nanotron
- Evaluation suite with lighteval
- Synthetic data generation using distilabel (powers our new SFT dataset HuggingFaceTB/smoltalk)
- Post-training scripts with TRL & the alignment handbook
- On-device tools with llama.cpp for summarization, rewriting & agents
Apache 2.0 licensed. V2 pre-training data mix coming soon!
Which other tools should we add next?
updated
4
models
3 days ago