Models, including the pretrained sparse autoencoders:
huggingface.co/collections/...
huggingface.co/collections/...
SlideOn & mSlideOn - a lightonai Collection
A collection of pretrained sparse autoencoders (SAEs) and fine-tuned sparse retrievers for English and multilingual, long-context, code retrieval
huggingface.co
October 20, 2026 at 2:16 PM
Models, including the pretrained sparse autoencoders:
huggingface.co/collections/...
huggingface.co/collections/...
0.8B finetunes: huggingface.co/models?other...
Fine-tuned Models for lightonai/LightOnOCR-3-0.8B – Hugging Face
Explore machine learning models.
huggingface.co
October 12, 2026 at 5:45 PM
0.8B finetunes: huggingface.co/models?other...
📰 Reddit r/LocalLLaMA
lightonai/LightOnOCR-3-4B · Hugging Face
https://www.reddit.com/r/LocalLLaMA/comments/1x1jdsk/lightonailightonocr34b_hugging_fac#IA
#AI #ML #ML
lightonai/LightOnOCR-3-4B · Hugging Face
https://www.reddit.com/r/LocalLLaMA/comments/1x1jdsk/lightonailightonocr34b_hugging_fac#IA
#AI #ML #ML
October 9, 2026 at 3:01 PM
📰 Reddit r/LocalLLaMA
lightonai/LightOnOCR-3-4B · Hugging Face
https://www.reddit.com/r/LocalLLaMA/comments/1x1jdsk/lightonailightonocr34b_hugging_fac#IA
#AI #ML #ML
lightonai/LightOnOCR-3-4B · Hugging Face
https://www.reddit.com/r/LocalLLaMA/comments/1x1jdsk/lightonailightonocr34b_hugging_fac#IA
#AI #ML #ML
I quite like github.com/lightonai/fa...!
There's some docs here: huggingface.co/blog/multi-v...
And indeed, FAISS won't work, as it's not designed for MaxSim and multi-vector embeddings indeed.
There's some docs here: huggingface.co/blog/multi-v...
And indeed, FAISS won't work, as it's not designed for MaxSim and multi-vector embeddings indeed.
GitHub - lightonai/fast-plaid: High-Performance Engine for Multi-Vector Search
High-Performance Engine for Multi-Vector Search. Contribute to lightonai/fast-plaid development by creating an account on GitHub.
github.com
October 7, 2026 at 9:33 PM
I quite like github.com/lightonai/fa...!
There's some docs here: huggingface.co/blog/multi-v...
And indeed, FAISS won't work, as it's not designed for MaxSim and multi-vector embeddings indeed.
There's some docs here: huggingface.co/blog/multi-v...
And indeed, FAISS won't work, as it's not designed for MaxSim and multi-vector embeddings indeed.
🔌 colgrep: Semantic code search for your terminal. Combines regex filtering with semantic ranking. All local — your code never leaves your machine.
📦 https://github.com/lightonai/next-plaid
🔗 https://github.com/javimosch/supercli
#colgrep #supercli
📦 https://github.com/lightonai/next-plaid
🔗 https://github.com/javimosch/supercli
#colgrep #supercli
September 1, 2026 at 2:44 AM
🔌 colgrep: Semantic code search for your terminal. Combines regex filtering with semantic ranking. All local — your code never leaves your machine.
📦 https://github.com/lightonai/next-plaid
🔗 https://github.com/javimosch/supercli
#colgrep #supercli
📦 https://github.com/lightonai/next-plaid
🔗 https://github.com/javimosch/supercli
#colgrep #supercli
Three checkpoints are affected, all ColBERT-Zero:
- lightonai/ColBERT-Zero
- lightonai/ColBERT-Zero-supervised
- lightonai/ColBERT-Zero-unsupervised
Restoring the prefix takes ColBERT-Zero from 0.6569 to 0.6824 NanoBEIR nDCG@10.
Indexed with one of these? Re-encode.
- lightonai/ColBERT-Zero
- lightonai/ColBERT-Zero-supervised
- lightonai/ColBERT-Zero-unsupervised
Restoring the prefix takes ColBERT-Zero from 0.6569 to 0.6824 NanoBEIR nDCG@10.
Indexed with one of these? Re-encode.
August 31, 2026 at 8:38 AM
Three checkpoints are affected, all ColBERT-Zero:
- lightonai/ColBERT-Zero
- lightonai/ColBERT-Zero-supervised
- lightonai/ColBERT-Zero-unsupervised
Restoring the prefix takes ColBERT-Zero from 0.6569 to 0.6824 NanoBEIR nDCG@10.
Indexed with one of these? Re-encode.
- lightonai/ColBERT-Zero
- lightonai/ColBERT-Zero-supervised
- lightonai/ColBERT-Zero-unsupervised
Restoring the prefix takes ColBERT-Zero from 0.6569 to 0.6824 NanoBEIR nDCG@10.
Indexed with one of these? Re-encode.
🔧 Sentence Transformers v6.0.1 is out: a patch release fixing multi-vector checkpoints that carry both a [Q]/[D] prefix and a prompt.
This only affected you if you used lightonai/ColBERT-Zero via Sentence Transformers, no other models affected AFAIK 🧵
This only affected you if you used lightonai/ColBERT-Zero via Sentence Transformers, no other models affected AFAIK 🧵
August 31, 2026 at 8:38 AM
🔧 Sentence Transformers v6.0.1 is out: a patch release fixing multi-vector checkpoints that carry both a [Q]/[D] prefix and a prompt.
This only affected you if you used lightonai/ColBERT-Zero via Sentence Transformers, no other models affected AFAIK 🧵
This only affected you if you used lightonai/ColBERT-Zero via Sentence Transformers, no other models affected AFAIK 🧵
lightonai/mLateOn and mDenseOn are multilingual extensions of LateOn and DenseOn — eight languages plus English, same backbone.
On English retrieval, both beat the English-only models they extend: 23rd of 197 vs 25th, and 28th vs 31st.
Added by NohTow, results by paulomouraj.
On English retrieval, both beat the English-only models they extend: 23rd of 197 vs 25th, and 28th vs 31st.
Added by NohTow, results by paulomouraj.
August 14, 2026 at 1:24 PM
lightonai/mLateOn and mDenseOn are multilingual extensions of LateOn and DenseOn — eight languages plus English, same backbone.
On English retrieval, both beat the English-only models they extend: 23rd of 197 vs 25th, and 28th vs 31st.
Added by NohTow, results by paulomouraj.
On English retrieval, both beat the English-only models they extend: 23rd of 197 vs 25th, and 28th vs 31st.
Added by NohTow, results by paulomouraj.
Model link: huggingface.co/lightonai/GT...
GTE-ModernColBERT is trained on top of the GTE-ColBERT model using knowledge distillation on the MS MARCO dataset and is the first SOTA model trained using PyLate!
Get started with PyLate using the documentation:
lightonai.github.io/pylate/
GTE-ModernColBERT is trained on top of the GTE-ColBERT model using knowledge distillation on the MS MARCO dataset and is the first SOTA model trained using PyLate!
Get started with PyLate using the documentation:
lightonai.github.io/pylate/
lightonai/GTE-ModernColBERT-v1 · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
huggingface.co
April 30, 2025 at 2:42 PM
Model link: huggingface.co/lightonai/GT...
GTE-ModernColBERT is trained on top of the GTE-ColBERT model using knowledge distillation on the MS MARCO dataset and is the first SOTA model trained using PyLate!
Get started with PyLate using the documentation:
lightonai.github.io/pylate/
GTE-ModernColBERT is trained on top of the GTE-ColBERT model using knowledge distillation on the MS MARCO dataset and is the first SOTA model trained using PyLate!
Get started with PyLate using the documentation:
lightonai.github.io/pylate/
Model link: huggingface.co/lightonai/mo...
ModernBERT-embed-large is trained using the same (two-stage training) recipe as its smaller sibling and expectedly increases the performance, reaching +1.22 in MTEB average
ModernBERT-embed-large is trained using the same (two-stage training) recipe as its smaller sibling and expectedly increases the performance, reaching +1.22 in MTEB average
January 14, 2025 at 3:32 PM
Model link: huggingface.co/lightonai/mo...
ModernBERT-embed-large is trained using the same (two-stage training) recipe as its smaller sibling and expectedly increases the performance, reaching +1.22 in MTEB average
ModernBERT-embed-large is trained using the same (two-stage training) recipe as its smaller sibling and expectedly increases the performance, reaching +1.22 in MTEB average
If you are not familiar with PyLate, this is a modular library based on sentence-transformers to train and explore around multi-vectors retrieval models
You can find it there: github.com/lightonai/py...
As always, thanks to @raphaelsty.bsky.social for developing this with me!
You can find it there: github.com/lightonai/py...
As always, thanks to @raphaelsty.bsky.social for developing this with me!
GitHub - lightonai/pylate: Late Interaction Models Training & Retrieval
Late Interaction Models Training & Retrieval. Contribute to lightonai/pylate development by creating an account on GitHub.
github.com
November 26, 2024 at 3:29 PM
If you are not familiar with PyLate, this is a modular library based on sentence-transformers to train and explore around multi-vectors retrieval models
You can find it there: github.com/lightonai/py...
As always, thanks to @raphaelsty.bsky.social for developing this with me!
You can find it there: github.com/lightonai/py...
As always, thanks to @raphaelsty.bsky.social for developing this with me!
This colgrep thing given to an agent as an MCP tool is IMO worth your time.
Mine is a cheap hack variant using local embeddings and a reranker and it’s so much more efficient than grep.
Tool description matters a lot (gotta expose it so the agent understands how to reach for it) but it’s great.
Mine is a cheap hack variant using local embeddings and a reranker and it’s so much more efficient than grep.
Tool description matters a lot (gotta expose it so the agent understands how to reach for it) but it’s great.
GitHub - lightonai/next-plaid: NextPlaid, ColGREP: Multi-vector search, from database to coding agents.
NextPlaid, ColGREP: Multi-vector search, from database to coding agents. - lightonai/next-plaid
github.com
April 16, 2026 at 3:08 AM
This colgrep thing given to an agent as an MCP tool is IMO worth your time.
Mine is a cheap hack variant using local embeddings and a reranker and it’s so much more efficient than grep.
Tool description matters a lot (gotta expose it so the agent understands how to reach for it) but it’s great.
Mine is a cheap hack variant using local embeddings and a reranker and it’s so much more efficient than grep.
Tool description matters a lot (gotta expose it so the agent understands how to reach for it) but it’s great.
LightOnOCR-1B: The Case for End-to-End and Efficient Domain-Specific Vision-Language Models for OCR
轻量级型字元识别模型
博客： huggingface.co/blog/lighton...
Hugging Face: huggingface.co/lightonai/Li...
轻量级型字元识别模型
博客： huggingface.co/blog/lighton...
Hugging Face: huggingface.co/lightonai/Li...
January 31, 2026 at 4:05 PM
LightOnOCR-1B: The Case for End-to-End and Efficient Domain-Specific Vision-Language Models for OCR
轻量级型字元识别模型
博客： huggingface.co/blog/lighton...
Hugging Face: huggingface.co/lightonai/Li...
轻量级型字元识别模型
博客： huggingface.co/blog/lighton...
Hugging Face: huggingface.co/lightonai/Li...
A semantic Code Search CLI but with grep filters Article URL: https://github.com/lightonai/next-plaid Comments URL: https://news.ycombinator.com/item?id=47212886 Points: 1 # Comments: 1
Origin | Interest | Match
Origin | Interest | Match
GitHub - lightonai/next-plaid: NextPlaid, ColGREP: Multi-vector search, from database to coding agents.
NextPlaid, ColGREP: Multi-vector search, from database to coding agents. - lightonai/next-plaid
github.com
March 2, 2026 at 2:06 AM
ColGREP - Fast semantic #code #search for terminal and #codeagents using multi-vector & late chunking technique. By @lightonai.bsky.social
Combines #regex filtering with semantic ranking. Local-only.
#OpenSource Apache 2.0 Lic
#GREP #Search
Combines #regex filtering with semantic ranking. Local-only.
#OpenSource Apache 2.0 Lic
#GREP #Search
GitHub - lightonai/next-plaid: NextPlaid, ColGREP: Multi-vector search, from database to coding agents.
NextPlaid, ColGREP: Multi-vector search, from database to coding agents. - lightonai/next-plaid
github.com
May 7, 2026 at 8:03 PM
ColGREP - Fast semantic #code #search for terminal and #codeagents using multi-vector & late chunking technique. By @lightonai.bsky.social
Combines #regex filtering with semantic ranking. Local-only.
#OpenSource Apache 2.0 Lic
#GREP #Search
Combines #regex filtering with semantic ranking. Local-only.
#OpenSource Apache 2.0 Lic
#GREP #Search
Or the models: huggingface.co/collections/...
LightOn-rerank - a lightonai Collection
LightOn-rerank models are unified cross-encoder rerankers: Qwen3.5 LoRAs scoring both text passages and document page images against a query.
huggingface.co
July 17, 2026 at 2:18 PM
Or the models: huggingface.co/collections/...
All models, including intermediate checkpoints for every training phase and configuration, are released under Apache 2.0. The strongest model, lightonai/ColBERT-Zero, is the new strongest late interaction model.
🧵
🧵
February 23, 2026 at 2:20 PM
All models, including intermediate checkpoints for every training phase and configuration, are released under Apache 2.0. The strongest model, lightonai/ColBERT-Zero, is the new strongest late interaction model.
🧵
🧵
Beyond the models and ColGREP, they've also released the processed full datasets (CoRNStack, CoIR), which should also be useful for other code retrieval training: huggingface.co/collections/...
🧵
🧵
LateOn-Code 💻 - a lightonai Collection
State-of-the-art late interaction code retrieval models
huggingface.co
February 12, 2026 at 7:30 PM
Beyond the models and ColGREP, they've also released the processed full datasets (CoRNStack, CoIR), which should also be useful for other code retrieval training: huggingface.co/collections/...
🧵
🧵
I'm very proud to see these models release. PyLate is a wonderful project that builds on top of Sentence Transformers very nicely, resulting in a wonderful stack.
See here for example the full finetuning code here: github.com/lightonai/py...
🧵
See here for example the full finetuning code here: github.com/lightonai/py...
🧵
pylate/examples/train/lateon_code/fine_tuning.py at main · lightonai/pylate
Late Interaction Models Training & Retrieval. Contribute to lightonai/pylate development by creating an account on GitHub.
github.com
February 12, 2026 at 7:30 PM
I'm very proud to see these models release. PyLate is a wonderful project that builds on top of Sentence Transformers very nicely, resulting in a wonderful stack.
See here for example the full finetuning code here: github.com/lightonai/py...
🧵
See here for example the full finetuning code here: github.com/lightonai/py...
🧵
LateOn-Code 💻 - a lightonai Collection
State-of-the-art late interaction code retrieval models
huggingface.co
February 12, 2026 at 7:30 PM
Multilingual NanoBEIR Support:
You can now use community translations of the tiny NanoBEIR retrieval benchmark instead of only the English one, by passing `dataset_id`, e.g. `dataset_id="lightonai/NanoBEIR-de"` for the German benchmark.
🧵
You can now use community translations of the tiny NanoBEIR retrieval benchmark instead of only the English one, by passing `dataset_id`, e.g. `dataset_id="lightonai/NanoBEIR-de"` for the German benchmark.
🧵
December 11, 2025 at 2:46 PM
Multilingual NanoBEIR Support:
You can now use community translations of the tiny NanoBEIR retrieval benchmark instead of only the English one, by passing `dataset_id`, e.g. `dataset_id="lightonai/NanoBEIR-de"` for the German benchmark.
🧵
You can now use community translations of the tiny NanoBEIR retrieval benchmark instead of only the English one, by passing `dataset_id`, e.g. `dataset_id="lightonai/NanoBEIR-de"` for the German benchmark.
🧵
