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pcuenq 
posted an update 3 days ago
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2350
👉 What happened in AI in 2025? 👈

We prepared the 2025 version of the HF AI Timeline Grid, highlighting open vs API-based model releases, and allowing you to browse and filter by access, modality, and release type!

Play with it here:
2025-ai-timeline/2025-ai-timeline

Here's my personal quarterly TL;DR:

1️⃣ Q1 — Learning to Reason
Deepseek not only releases a top-notch reasoning model, but shows how to train them and compete with closed frontier models. OpenAI debuts Deep Research.

Significant milestones: DeepSeek R1 & R1-Zero, Qwen 2.5 VL, OpenAI Deep Research, Gemini 2.5 Pro (experimental)

2️⃣ Q2 — Multimodality and Coding
More LLMs embrace multimodality by default, and there's a surge in coding agents. Strong vision, audio, and generative models emerge.

Significant milestones: Llama 4, Qwen 3, Imagen 4, OpenAI Codex, Google Jules, Claude 4

3️⃣ Q3 — "Gold" rush, OpenAI opens up, the community goes bananas
Flagship models get gold in Math olympiads and hard benchmarks. OpenAI releases strong open source models and Google releases the much anticipated nano-banana for image generation and editing. Agentic workflows become commonplace.

Significant milestones: Gemini and OpenAI IMO Gold, gpt-oss, Gemini 2.5 Flash Image, Grok 4, Claude Sonnet 4.5

4️⃣ Q4 — Mistral returns, leaderboard hill-climbing
Mistral is back with updated model families. All labs release impressive models to wrap up the year!

Significant milestones: Claude Opus 4.5, DeepSeek Math V2, FLUX 2, GPT 5.1, Kimi K2 Thinking, Nano Banana Pro, GLM 4.7, Gemini 3, Mistral 3, MiniMax M2.1 🤯

Credits
🙏 NHLOCAL for the source data https://github.com/NHLOCAL/AiTimeline

🫡 @reach-vb for the original idea, design and recipe

🙌 @ariG23498 and yours truly for compiling and verifying the 2025 edition

🥳 Here's to 2026, wishing it becomes the best year ever for open releases and on-device-first use-cases! 🥂
  • 1 reply
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osanseviero 
authored a paper 3 months ago
loubnabnl 
authored a paper 7 months ago
loubnabnl 
posted an update 8 months ago
pcuenq 
authored a paper 9 months ago
loubnabnl 
authored a paper 9 months ago
bstadt 
authored 2 papers 9 months ago
osanseviero 
authored a paper 10 months ago
loubnabnl 
authored a paper 11 months ago
loubnabnl 
posted an update about 1 year ago
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3744
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?
loubnabnl 
authored a paper over 1 year ago
loubnabnl 
posted an update over 1 year ago
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5911
🍷 FineWeb technical report is out and so is 📚 FineWeb-Edu, a 1.3 trillion tokens dataset that outperforms all other open web datasets, with remarkable improvements on educational benchmarks such as MMLU, ARC, and OpenBookQA.

Technical report: HuggingFaceFW/blogpost-fineweb-v1
Dataset: HuggingFaceFW/fineweb-edu

We used Llama 3 generations to train an educational quality classifier, filtering the 15 trillion tokens of FineWeb to select only those with high educational value (an approach also used in Llama 3 and Phi-3 training datasets). We're releasing both FineWeb-Edu and the classifier, along with a larger, less heavily filtered version containing 5.4 trillion tokens.

You can find more details about the dataset and the experiments we ran in the FineWeb technical report, It's a 45-minute read but it contains all the secret sauce for building high quality web datasets.

Enjoy!
loubnabnl 
authored a paper over 1 year ago
pcuenq 
posted an update over 1 year ago
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10266
OpenELM in Core ML

Apple recently released a set of efficient LLMs in sizes varying between 270M and 3B parameters. Their quality, according to benchmarks, is similar to OLMo models of comparable size, but they required half the pre-training tokens because they use layer-wise scaling, where the number of attention heads increases in deeper layers.

I converted these models to Core ML, for use on Apple Silicon, using this script: https://gist.github.com/pcuenca/23cd08443460bc90854e2a6f0f575084. The converted models were uploaded to this community in the Hub for anyone that wants to integrate inside their apps: corenet-community/openelm-core-ml-6630c6b19268a5d878cfd194

The conversion was done with the following parameters:
- Precision: float32.
- Sequence length: fixed to 128.

With swift-transformers (https://github.com/huggingface/swift-transformers), I'm getting about 56 tok/s with the 270M on my M1 Max, and 6.5 with the largest 3B model. These speeds could be improved by converting to float16. However, there's some precision loss somewhere and generation doesn't work in float16 mode yet. I'm looking into this and will keep you posted! Or take a look at this issue if you'd like to help: https://github.com/huggingface/swift-transformers/issues/95

I'm also looking at optimizing inference using an experimental kv cache in swift-transformers. It's a bit tricky because the layers have varying number of attention heads, but I'm curious to see how much this feature can accelerate performance in this model family :)

Regarding the instruct fine-tuned models, I don't know the chat template that was used. The models use the Llama 2 tokenizer, but the Llama 2 chat template, or the default Alignment Handbook one that was used to train, are not recognized. Any ideas on this welcome!
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osanseviero 
posted an update over 1 year ago
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15862
Diaries of Open Source. Part 15 🤗

🕵️‍♀️Idefics 2 is out, a multimodal open-source model with very nice capabilities
Models, demo, and datasets: HuggingFaceM4/idefics2-661d1971b7c50831dd3ce0fe
Blog: https://hf.co/blog/idefics2

💾Snowflake released snowflake-arctic-embed, a family of powerful small embedding models
Model: Snowflake/snowflake-arctic-embed-m
Blog: https://www.snowflake.com/blog/introducing-snowflake-arctic-embed-snowflakes-state-of-the-art-text-embedding-family-of-models/

✨Pile-T5, EleutherAI's T5 model trained on 2T tokens
Blog: https://blog.eleuther.ai/pile-t5/
Models: EleutherAI/pile-t5-65a76a0d0022dd270b385a66
GitHub: https://github.com/EleutherAI/improved-t5

🤖CodeQwen1.5-7B base and chat models. Models trained on 3T tokens strong benchmark results for code generation, editing and SQL
Blog post: https://qwenlm.github.io/blog/codeqwen1.5/
Demo: https://hf.co/spaces/Qwen/CodeQwen1.5-7b-Chat-demo
Models: Qwen/CodeQwen1.5-7B and Qwen/CodeQwen1.5-7B-Chat

Misc
🦉 DocOwl1.5: Unified Stucture Learning for OCR-free Document Understanding mPLUG/DocOwl
👀Cerule - a tiny Vision LM model Tensoic/Cerule-v0.1
ChemLLM - a LLM for chemistry and molecule science ⚗️https://hf.co/AI4Chem/ChemLLM-7B-Chat-1.5-DPO
Distil Whisper Large
📝New pdf/OCR datasets with 19 samples pixparse/pdf-document-ocr-datasets-660701430b0346f97c4bc628
🔥Gretel AI high quality text-to-sql synthetic dataset gretelai/synthetic_text_to_sql
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osanseviero 
posted an update over 1 year ago
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11397
Diaries of Open Source. Part 14 🤗

🔥CohereForAI releases Command R+, an open 104B model with:
- Tool usage capabilities
- Specialized in RAGs
- Multilingual
It's one of the first models to surpass GPT-4 in the lmsys arena, check it out!
Model: https://hf.co/CohereForAI/c4ai-command-r-plus
Official demo: https://hf.co/spaces/CohereForAI/c4ai-command-r-plus
Quantized: https://hf.co/CohereForAI/c4ai-command-r-plus-4bit

🎉Google releases a new version of their Gemma instruct models, with improved quality, nicer to converse, and a fancier RL algorithm. The model is similar to Llama 2 70B in the Chat Arena!
Models: google/gemma-release-65d5efbccdbb8c4202ec078b
Try it out in HuggingChat https://hf.co/chat/models/google/gemma-1.1-7b-it

🪄VoiceCraft, a speech editing and TTS SOTA open model
Paper: VoiceCraft: Zero-Shot Speech Editing and Text-to-Speech in the Wild (2403.16973)
Model: pyp1/VoiceCraft

💻Google released CodeGemma, a family of code generation, completion, and chat models
Blog post: https://hf.co/blog/codegemma
Models: google/codegemma-release-66152ac7b683e2667abdee11
Report: https://storage.googleapis.com/deepmind-media/gemma/codegemma_report.pdf

Misc models:
🦖T-Rex2, a very powerful object detection model for many applications https://github.com/IDEA-Research/T-Rex
👀 CT-RATE : A 3D dataset paired with text reports ibrahimhamamci/CT-RATE
🐙Octopus v2: a Gemma-based model trained for Android API - extremely fast, better than Llama+RAG, great results https://hf.co/NexaAIDev/Octopus-v2
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osanseviero 
posted an update almost 2 years ago
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2409
Diaries of Open Source. Part 13 🤗

🤏Two different bitnet 1.5 open-source replications
Original paper: The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits (2402.17764)
1bitllm experiment: https://hf.co/blog/joey00072/experiments-with-bitnet-1-5
NousResearch experiment NousResearch/OLMo-Bitnet-1B

🥳Tiny and large multimodal models great for embeddings
GitHub: https://github.com/unum-cloud/uform
Encoders: https://hf.co/collections/unum-cloud/multimodal-encoders-660553903617c5297eb16838
ONNX weights: https://hf.co/collections/unum-cloud/uform-vl-english-large-onnx-66055a57c182d846f3bc1949

📜 SMPLer-X: Expressive Human Pose and Shape Estimation
Project website: https://caizhongang.com/projects/SMPLer-X/
Demo: caizhongang/SMPLer-X
Paper: SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation (2309.17448)

🧙GeoWizard: 3D Geometry Estimation
Project website: https://fuxiao0719.github.io/projects/geowizard/
Demo: lemonaddie/geowizard

Misc models and datasets
- Dolphin-2.8-mistral-7b-v0.2 https://hf.co/cognitivecomputations/dolphin-2.8-mistral-7b-v02
- Hermes-2-Pro-11B, a self-frankenmerge 11B variant mattshumer/Hermes-2-Pro-11B
- Large conversational dataset based on Usenet data in the Italian language mii-community/UsenetArchiveIT-conversations
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osanseviero 
posted an update almost 2 years ago
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3688
Diaries of Open Source. Part 12 🤗

🚀Alibaba releases Qwen1.5-MoE-A2.7B, an interesting MoE with 2.7B activated parameters and 64 experts
Blog https://qwenlm.github.io/blog/qwen-moe/
Demo: https://hf.co/spaces/Qwen/qwen1.5-MoE-A2.7B-Chat-demo
Models:
Qwen
GitHub: https://github.com/QwenLM/Qwen1.5

🎵VoiceCraft, SOTA speech editing and text to speech
GitHub: https://github.com/jasonppy/VoiceCraft
Model: pyp1/VoiceCraft

🐍 AI21Labs release Jamba, an SSM-Transformer, pretrained MoE which allows a large context window (256K) and high throughput
Blog https://www.ai21.com/blog/announcing-jamba
Model ai21labs/Jamba-v0.1

✨ Berkeley releases Starling-LM-7B, an RLHF-ed model, and -RM-34B, a Yi-based reward model very good for its size
Starling Beta: Nexusflow/Starling-LM-7B-beta
Starling RM: Nexusflow/Starling-RM-34B

🖥️Stability releases Stable Code Instruct 3B, an instruct model for code generation
Blog: https://stability.ai/news/introducing-stable-code-instruct-3b
Demo: stabilityai/stable-code-instruct-3b
Report: https://stability.ai/s/Stable_Code_TechReport_release.pdf

📚Common Corpus: the largest public domain dataset for training LLMs
Blog: https://hf.co/blog/Pclanglais/common-corpus
Dataset: https://hf.co/collections/PleIAs/common-corpus-65d46e3ea3980fdcd66a5613

Misc:
⚡GaLore: a very memory-efficient technique that allows pretraining models in consumer GPUs https://hf.co/blog/galore
Moirai
📈Moirai, foundation models for time series forecasting https://hf.co/collections/Salesforce/moirai-10-r-models-65c8d3a94c51428c300e0742
🔥 Mistral-ORPO-Capybara-7K, a high-quality Mistral fine-tune using ORPO, a new alignment technique kaist-ai/mistral-orpo-capybara-7k
🤯APISR, an anime super-resolution upscaling model HikariDawn/APISR
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osanseviero 
posted an update almost 2 years ago
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2163
Diaries of Open Source. Part 11 🚀

🚀Databricks release DBRX, potentially the best open access model! A 132B Mixture of Experts with 36B active params and trained on 12 trillion tokens
Blog: https://www.databricks.com/blog/introducing-dbrx-new-state-art-open-llm
Base and instruct models: databricks/dbrx-6601c0852a0cdd3c59f71962
Demo: https://hf.co/spaces/databricks/dbrx-instruct

🤏1-bit and 2-bit quantization exploration using HQQ+
Blog post: https://mobiusml.github.io/1bit_blog/
Models: https://hf.co/collections/mobiuslabsgmbh/llama2-7b-hqq-6604257a96fc8b9c4e13e0fe
GitHub: https://github.com/mobiusml/hqq

📚Cosmopedia: a large-scale synthetic dataset for pre-training - it includes 25 billion tokens and 30 million files
Dataset: HuggingFaceTB/cosmopedia
Blog: https://hf.co/blog/cosmopedia

⭐Mini-Gemini: multi-modal VLMs, from 2B to 34B
Models: https://hf.co/collections/YanweiLi/mini-gemini-6603c50b9b43d044171d0854
Paper: Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models (2403.18814)
GitHub: https://github.com/dvlab-research/MiniGemini

🔥VILA - On Pre-training for VLMs
Models: Efficient-Large-Model/vila-on-pre-training-for-visual-language-models-65d8022a3a52cd9bcd62698e
Paper: VILA: On Pre-training for Visual Language Models (2312.07533)

Misc
👀 FeatUp: a framework for image features at any resolution: mhamilton723/FeatUp FeatUp: A Model-Agnostic Framework for Features at Any Resolution (2403.10516)
🍞ColBERTus Maxiums, a colbertialized embedding model mixedbread-ai/mxbai-colbert-large-v1
🖌️Semantic Palette, a new drawing paradigm https://hf.co/spaces/ironjr/SemanticPalette
🧑‍⚕️HistoGPT, a vision model that generates accurate pathology reports marr-peng-lab/histogpt https://www.medrxiv.org/content/10.1101/2024.03.15.24304211v1
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