FineVision: Open Data Is All You Need
Paper
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2510.17269
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Published
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59
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ariG23498
authored
a
paper
8 days ago
Post
4384
LiquidAI/LFM2-8B-A1B just dropped!
8.3B params with only 1.5B active/token 🚀
> Quality ≈ 3–4B dense, yet faster than Qwen3-1.7B
> MoE designed to run on phones/laptops (llama.cpp / vLLM)
> Pre-trained on 12T tokens → strong math/code/IF
8.3B params with only 1.5B active/token 🚀
> Quality ≈ 3–4B dense, yet faster than Qwen3-1.7B
> MoE designed to run on phones/laptops (llama.cpp / vLLM)
> Pre-trained on 12T tokens → strong math/code/IF
- 1 reply
Post
3528
⚛️ New drop of tiny task-specific models!
Want to do data extraction, translation, RAG, tool use, or math on a Raspberry Pi? We got you covered! ✅
These tiny models were fine-tuned to perform narrow tasks extremely well, making them competitive with much larger models.
You can deploy them today on-device or even on GPUs for big data operations!
LiquidAI/liquid-nanos-68b98d898414dd94d4d5f99a
Want to do data extraction, translation, RAG, tool use, or math on a Raspberry Pi? We got you covered! ✅
These tiny models were fine-tuned to perform narrow tasks extremely well, making them competitive with much larger models.
You can deploy them today on-device or even on GPUs for big data operations!
LiquidAI/liquid-nanos-68b98d898414dd94d4d5f99a
- 1 reply
gusthema
authored
3
papers
about 1 month ago
osanseviero
authored
a
paper
about 1 month ago
ssmoot
authored
a
paper
about 1 month ago
Post
6238
We're kick-starting the process of Transformers v5, with
@ArthurZ
and
@cyrilvallez
!
v5 should be significant: we're using it as a milestone for performance optimizations, saner defaults, and a much cleaner code base worthy of 2025.
Fun fact: v4.0.0-rc-1 came out on Nov 19, 2020, nearly five years ago!
v5 should be significant: we're using it as a milestone for performance optimizations, saner defaults, and a much cleaner code base worthy of 2025.
Fun fact: v4.0.0-rc-1 came out on Nov 19, 2020, nearly five years ago!
- 6 replies
Post
910
New post is live!
This time we cover some major updates to
🤗
This time we cover some major updates to
transformers.🤗
-
- 1 reply
mrpeerat
authored
6
papers
2 months ago
SEA-HELM: Southeast Asian Holistic Evaluation of Language Models
Paper
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2502.14301
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Published
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2
Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia
Paper
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2503.07920
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Published
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101
SEA-LION: Southeast Asian Languages in One Network
Paper
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2504.05747
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Published
Language Surgery in Multilingual Large Language Models
Paper
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2506.12450
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Published
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16
Mangosteen: An Open Thai Corpus for Language Model Pretraining
Paper
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2507.14664
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Published
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7
WangchanThaiInstruct: An instruction-following Dataset for Culture-Aware, Multitask, and Multi-domain Evaluation in Thai
Paper
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2508.15239
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Published
danielhanchen
posted
an
update
2 months ago
Post
5825
Run DeepSeek-V3.1 locally on 170GB RAM with Dynamic 1-bit GGUFs!🐋
GGUFs: unsloth/DeepSeek-V3.1-GGUF
The 715GB model gets reduced to 170GB (-80% size) by smartly quantizing layers.
The 1-bit GGUF passes all our code tests & we fixed the chat template for llama.cpp supported backends.
Guide: https://docs.unsloth.ai/basics/deepseek-v3.1
GGUFs: unsloth/DeepSeek-V3.1-GGUF
The 715GB model gets reduced to 170GB (-80% size) by smartly quantizing layers.
The 1-bit GGUF passes all our code tests & we fixed the chat template for llama.cpp supported backends.
Guide: https://docs.unsloth.ai/basics/deepseek-v3.1
Post
8208
Okay this is insane... WebGPU-accelerated semantic video tracking, powered by DINOv3 and Transformers.js! 🤯
Demo (+ source code): webml-community/DINOv3-video-tracking
This will revolutionize AI-powered video editors... which can now run 100% locally in your browser, no server inference required (costs $0)! 😍
How does it work? 🤔
1️⃣ Generate and cache image features for each frame
2️⃣ Create a list of embeddings for selected patch(es)
3️⃣ Compute cosine similarity between each patch and the selected patch(es)
4️⃣ Highlight those whose score is above some threshold
... et voilà! 🥳
You can also make selections across frames to improve temporal consistency! This is super useful if the object changes its appearance slightly throughout the video.
Excited to see what the community builds with it!
Demo (+ source code): webml-community/DINOv3-video-tracking
This will revolutionize AI-powered video editors... which can now run 100% locally in your browser, no server inference required (costs $0)! 😍
How does it work? 🤔
1️⃣ Generate and cache image features for each frame
2️⃣ Create a list of embeddings for selected patch(es)
3️⃣ Compute cosine similarity between each patch and the selected patch(es)
4️⃣ Highlight those whose score is above some threshold
... et voilà! 🥳
You can also make selections across frames to improve temporal consistency! This is super useful if the object changes its appearance slightly throughout the video.
Excited to see what the community builds with it!
- 1 reply
Post
6734
Liquid just released two 450M and 1.6B param VLMs!
They're super fast and leverage SigLIP2 NaFlex encoders to handle native resolutions without distortion. It's ideal for on-device deployment in constrained environments like phones.
It's available today on Hugging Face, with an inference and a fine-tuning Colab notebooks.
LiquidAI/LFM2-VL-450M
LiquidAI/LFM2-VL-1.6B
They're super fast and leverage SigLIP2 NaFlex encoders to handle native resolutions without distortion. It's ideal for on-device deployment in constrained environments like phones.
It's available today on Hugging Face, with an inference and a fine-tuning Colab notebooks.
LiquidAI/LFM2-VL-450M
LiquidAI/LFM2-VL-1.6B
Post
4362
The next generation of AI-powered websites is going to be WILD! 🤯
In-browser tool calling & MCP is finally here, allowing LLMs to interact with websites programmatically.
To show what's possible, I built a demo using Liquid AI's new LFM2 model, powered by 🤗 Transformers.js: LiquidAI/LFM2-WebGPU
As always, the demo is open source (which you can find under the "Files" tab), so I'm excited to see how the community builds upon this! 🚀
In-browser tool calling & MCP is finally here, allowing LLMs to interact with websites programmatically.
To show what's possible, I built a demo using Liquid AI's new LFM2 model, powered by 🤗 Transformers.js: LiquidAI/LFM2-WebGPU
As always, the demo is open source (which you can find under the "Files" tab), so I'm excited to see how the community builds upon this! 🚀
- 2 replies