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Adam Molnar PRO

lunarflu

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AI & ML interests

trust and safety 🤗 reach out on discord (lunarflu) if you have any questions: hf.co/discord/join

Recent Activity

reacted to prithivMLmods's post with 🤗 16 minutes ago

Try the Hugging Face Space demo for https://huggingface.co/Logics-MLLM/Logics-Parsing, the latest multimodal VLM from the Logics Team at Alibaba Group. It enables end-to-end document parsing with precise content extraction in markdown format, and it also generates a clean HTML representation of the document while preserving its logical structure. 🤗🔥 Additionally, I’ve integrated one of my recent works — https://huggingface.co/prithivMLmods/Gliese-OCR-7B-Post1.0 — which also excels at document comprehension. ⭐ Space / App : https://huggingface.co/spaces/prithivMLmods/Logics-Parsing-VLM 📄 Technical Report by the Logics Team, Alibaba Group : https://huggingface.co/papers/2509.19760 ⚡ Collections : https://huggingface.co/collections/prithivMLmods/multimodal-implementations-67c9982ea04b39f0608badb0 Other Pages: ➔ Multimodal VLMs - July'25 : https://huggingface.co/collections/prithivMLmods/multimodal-vlms-until-july25-688312e6b840e1e156f13027 ➔ Multimodal VLMs - Aug'25 : https://huggingface.co/collections/prithivMLmods/multimodal-vlms-aug25-68a56aac39fe8084f3c168bd ➔ VL caption — < Sep 15 ’25 : https://huggingface.co/collections/prithivMLmods/vl-caption-sep-15-25-68c7f6d737985c63c13e2391 . . . To know more about it, visit the app page or the respective model page!!

reacted to prithivMLmods's post with 👍 16 minutes ago

Try the Hugging Face Space demo for https://huggingface.co/Logics-MLLM/Logics-Parsing, the latest multimodal VLM from the Logics Team at Alibaba Group. It enables end-to-end document parsing with precise content extraction in markdown format, and it also generates a clean HTML representation of the document while preserving its logical structure. 🤗🔥 Additionally, I’ve integrated one of my recent works — https://huggingface.co/prithivMLmods/Gliese-OCR-7B-Post1.0 — which also excels at document comprehension. ⭐ Space / App : https://huggingface.co/spaces/prithivMLmods/Logics-Parsing-VLM 📄 Technical Report by the Logics Team, Alibaba Group : https://huggingface.co/papers/2509.19760 ⚡ Collections : https://huggingface.co/collections/prithivMLmods/multimodal-implementations-67c9982ea04b39f0608badb0 Other Pages: ➔ Multimodal VLMs - July'25 : https://huggingface.co/collections/prithivMLmods/multimodal-vlms-until-july25-688312e6b840e1e156f13027 ➔ Multimodal VLMs - Aug'25 : https://huggingface.co/collections/prithivMLmods/multimodal-vlms-aug25-68a56aac39fe8084f3c168bd ➔ VL caption — < Sep 15 ’25 : https://huggingface.co/collections/prithivMLmods/vl-caption-sep-15-25-68c7f6d737985c63c13e2391 . . . To know more about it, visit the app page or the respective model page!!

reacted to prithivMLmods's post with ❤️ 16 minutes ago

Try the Hugging Face Space demo for https://huggingface.co/Logics-MLLM/Logics-Parsing, the latest multimodal VLM from the Logics Team at Alibaba Group. It enables end-to-end document parsing with precise content extraction in markdown format, and it also generates a clean HTML representation of the document while preserving its logical structure. 🤗🔥 Additionally, I’ve integrated one of my recent works — https://huggingface.co/prithivMLmods/Gliese-OCR-7B-Post1.0 — which also excels at document comprehension. ⭐ Space / App : https://huggingface.co/spaces/prithivMLmods/Logics-Parsing-VLM 📄 Technical Report by the Logics Team, Alibaba Group : https://huggingface.co/papers/2509.19760 ⚡ Collections : https://huggingface.co/collections/prithivMLmods/multimodal-implementations-67c9982ea04b39f0608badb0 Other Pages: ➔ Multimodal VLMs - July'25 : https://huggingface.co/collections/prithivMLmods/multimodal-vlms-until-july25-688312e6b840e1e156f13027 ➔ Multimodal VLMs - Aug'25 : https://huggingface.co/collections/prithivMLmods/multimodal-vlms-aug25-68a56aac39fe8084f3c168bd ➔ VL caption — < Sep 15 ’25 : https://huggingface.co/collections/prithivMLmods/vl-caption-sep-15-25-68c7f6d737985c63c13e2391 . . . To know more about it, visit the app page or the respective model page!!

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Organizations

upvoted a collection 3 days ago

Materials

Welcome to IBM’s multi-modal foundation model for materials, FM4M, designed to support and advance research in materials science and chemistry. • 12 items • Updated 4 days ago • 5

upvoted an article 8 days ago

Article

There is no such thing as a tokenizer-free lunch

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9 days ago

• 71

upvoted 12 articles 10 days ago

Article

Make your ZeroGPU Spaces go brrr with PyTorch ahead-of-time compilation

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Sep 2

• 66

Article

Welcome EmbeddingGemma, Google's new efficient embedding model

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and 5 others •

about 1 month ago

• 231

Article

mmBERT: ModernBERT goes Multilingual

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and 5 others •

25 days ago

• 105

Article

Jupyter Agents: training LLMs to reason with notebooks

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and 2 others •

24 days ago

• 46

Article

Tricks from OpenAI gpt-oss YOU 🫵 can use with transformers

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23 days ago

• 150

Article

Visible Watermarking with Gradio

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19 days ago

• 16

Article

`LeRobotDataset`: Bringing large-scale datasets to lerobot

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and 10 others •

18 days ago

• 35

Article

Public AI on Hugging Face Inference Providers 🔥

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and 5 others •

17 days ago

• 19

Article

Democratizing AI Safety with RiskRubric.ai

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16 days ago

• 15

Article

Scaleway on Hugging Face Inference Providers 🔥

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and 8 others •

15 days ago

• 19

Article

Gaia2 and ARE: Empowering the community to study agents

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and 10 others •

12 days ago

• 101

Article

Smol2Operator: Post-Training GUI Agents for Computer Use

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11 days ago

• 106

upvoted a collection 10 days ago

ByteDance Papers

ByteDance papers collection • 117 items • Updated 12 days ago • 13

upvoted a paper 11 days ago

TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models

Paper • 2109.10282 • Published Sep 21, 2021 • 11

upvoted 4 papers 14 days ago

Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap

Paper • 2410.07436 • Published Oct 9, 2024 • 1

LLM-Consensus: Multi-Agent Debate for Visual Misinformation Detection

Paper • 2410.20140 • Published Oct 26, 2024 • 1

PSyDUCK: Training-Free Steganography for Latent Diffusion

Paper • 2501.19172 • Published Jan 31 • 1

Fact-Checking with Contextual Narratives: Leveraging Retrieval-Augmented LLMs for Social Media Analysis

Paper • 2504.10166 • Published Apr 14 • 2