A Short Summary of Chinese AI Global Expansion
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Adina Yakefu
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reacted to
cfahlgren1's
post with 🔥
2 days ago
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1877
Why use Google Drive when you can have:
• Free storage with generous limits🆓
• Dataset Viewer (Sorting, Filtering, FTS) 🔍
• Third Party Library Support
• SQL Console 🟧
• Security 🔒
• Community, Reach, and Visibility 📈
It's a no brainer!
Check out our post on what you get instantly out of the box when you create a dataset.
https://huggingface.co/blog/researcher-dataset-sharing
• Free storage with generous limits🆓
• Dataset Viewer (Sorting, Filtering, FTS) 🔍
• Third Party Library Support
• SQL Console 🟧
• Security 🔒
• Community, Reach, and Visibility 📈
It's a no brainer!
Check out our post on what you get instantly out of the box when you create a dataset.
https://huggingface.co/blog/researcher-dataset-sharing
- 1 reply
reacted to
merve's
post with 🔥
2 days ago
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1747
Amazing past days at open ML, it's raining coding models, let's have a recap 🌧️ Find all models and datasets here
merve/nov-15-releases-67372d0ebdc354756a52ecd0
Models
💻 Coding: Qwen team released two Qwen2.5-Coder checkpoints of 32B and 7B. Infly released OpenCoder: 1.5B and 8B coding models with instruction SFT'd versions and their datasets! 💗
🖼️ Image/Video Gen: Alibaba vision lab released In-context LoRA -- 10 LoRA models on different themes based on Flux. Also Mochi the sota video generation model with A2.0 license now comes natively supported in diffusers 👏
🖼️ VLMs/Multimodal: NexaAIDev released Omnivision 968M a new vision language model aligned with DPO for reducing hallucinations, also comes with GGUF ckpts 👏 Microsoft released LLM2CLIP, a new CLIP-like model with longer context window allowing complex text inputs and better search
🎮 AGI?: Etched released Oasis 500M, a diffusion based open world model that takes keyboard input and outputs gameplay 🤯
Datasets
Common Corpus: A text dataset with 2T tokens with permissive license for EN/FR on various sources: code, science, finance, culture 📖
Models
💻 Coding: Qwen team released two Qwen2.5-Coder checkpoints of 32B and 7B. Infly released OpenCoder: 1.5B and 8B coding models with instruction SFT'd versions and their datasets! 💗
🖼️ Image/Video Gen: Alibaba vision lab released In-context LoRA -- 10 LoRA models on different themes based on Flux. Also Mochi the sota video generation model with A2.0 license now comes natively supported in diffusers 👏
🖼️ VLMs/Multimodal: NexaAIDev released Omnivision 968M a new vision language model aligned with DPO for reducing hallucinations, also comes with GGUF ckpts 👏 Microsoft released LLM2CLIP, a new CLIP-like model with longer context window allowing complex text inputs and better search
🎮 AGI?: Etched released Oasis 500M, a diffusion based open world model that takes keyboard input and outputs gameplay 🤯
Datasets
Common Corpus: A text dataset with 2T tokens with permissive license for EN/FR on various sources: code, science, finance, culture 📖
posted
an
update
2 days ago
Post
2322
Let’s dive into the exciting releases from the Chinese community last week 🔥🚀
More details 👉 https://huggingface.co/zh-ai-community
Code model:
✨Qwen 2.5 coder by Alibaba Qwen
Qwen/qwen25-coder-66eaa22e6f99801bf65b0c2f
✨OpenCoder by InflyAI - Fully open code model🙌
infly/opencoder-672cec44bbb86c39910fb55e
Image model:
✨Hunyuan3D-1.0 by Tencent
tencent/Hunyuan3D-1
MLLM:
✨JanusFlow by DeepSeek
deepseek-ai/JanusFlow-1.3B
deepseek-ai/JanusFlow-1.3B
✨Mono-InternVL-2B by OpenGVlab
OpenGVLab/Mono-InternVL-2B
Video model:
✨CogVideoX 1.5 by ChatGLM
THUDM/CogVideoX1.5-5B-SAT
Audio model:
✨Fish Agent by FishAudio
fishaudio/fish-agent-v0.1-3b
Dataset:
✨OPI dataset by BAAIBeijing
BAAI/OPI
More details 👉 https://huggingface.co/zh-ai-community
Code model:
✨Qwen 2.5 coder by Alibaba Qwen
Qwen/qwen25-coder-66eaa22e6f99801bf65b0c2f
✨OpenCoder by InflyAI - Fully open code model🙌
infly/opencoder-672cec44bbb86c39910fb55e
Image model:
✨Hunyuan3D-1.0 by Tencent
tencent/Hunyuan3D-1
MLLM:
✨JanusFlow by DeepSeek
deepseek-ai/JanusFlow-1.3B
deepseek-ai/JanusFlow-1.3B
✨Mono-InternVL-2B by OpenGVlab
OpenGVLab/Mono-InternVL-2B
Video model:
✨CogVideoX 1.5 by ChatGLM
THUDM/CogVideoX1.5-5B-SAT
Audio model:
✨Fish Agent by FishAudio
fishaudio/fish-agent-v0.1-3b
Dataset:
✨OPI dataset by BAAIBeijing
BAAI/OPI
posted
an
update
17 days ago
Post
669
The most upvoted papers from the Chinese community on the Daily Papers - October🔥
zh-ai-community/trending-papers-october-6723995e5d93f8e480928b8c
zh-ai-community/trending-papers-october-6723995e5d93f8e480928b8c
reacted to
merve's
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24 days ago
Post
2424
Lotus 🪷 is a new foundation model on monocular depth estimation ✨
Compared to previous diffusion-based MDE models, Lotus is modified for dense prediction tasks
Authors also released a model for normal prediction 🤗
Find everything in this collection merve/lotus-6718fb957dc1c85a47ca1210
Compared to previous diffusion-based MDE models, Lotus is modified for dense prediction tasks
Authors also released a model for normal prediction 🤗
Find everything in this collection merve/lotus-6718fb957dc1c85a47ca1210
reacted to
THUdyh's
post with 🔥
24 days ago
Post
3107
🔥🔥🔥Introducing Oryx-1.5!
A series of unified MLLMs with much stronger performance on all the image, video, and 3D benchmarks 😍
🛠️Github: https://github.com/Oryx-mllm/Oryx
🚀Model: THUdyh/oryx-15-6718c60763845525c2bba71d
🎨Demo: THUdyh/Oryx
👋Try the top-tier MLLM yourself!
👀Stay tuned for more explorations on MLLMs!
A series of unified MLLMs with much stronger performance on all the image, video, and 3D benchmarks 😍
🛠️Github: https://github.com/Oryx-mllm/Oryx
🚀Model: THUdyh/oryx-15-6718c60763845525c2bba71d
🎨Demo: THUdyh/Oryx
👋Try the top-tier MLLM yourself!
👀Stay tuned for more explorations on MLLMs!
reacted to
merve's
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24 days ago
Post
1630
Tencent released a new depth model that generates temporally consistent depth maps over videos ⏯️
Model: tencent/DepthCrafter
Demo: tencent/DepthCrafter
Paper: DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videos (2409.02095)
You don't need to input anything other than video itself, no need for optical flow or camera poses! 🤩
Model: tencent/DepthCrafter
Demo: tencent/DepthCrafter
Paper: DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videos (2409.02095)
You don't need to input anything other than video itself, no need for optical flow or camera poses! 🤩
reacted to
yuexiang96's
post with 🔥🚀
26 days ago
Post
2953
🌍 I’ve always had a dream of making AI accessible to everyone, regardless of location or language. However, current open MLLMs often respond in English, even to non-English queries!
🚀 Introducing Pangea: A Fully Open Multilingual Multimodal LLM supporting 39 languages! 🌐✨
https://neulab.github.io/Pangea/
https://arxiv.org/pdf/2410.16153
The Pangea family includes three major components:
🔥 Pangea-7B: A state-of-the-art multilingual multimodal LLM capable of 39 languages! Not only does it excel in multilingual scenarios, but it also matches or surpasses English-centric models like Llama 3.2, Molmo, and LlavaOneVision in English performance.
📝 PangeaIns: A 6M multilingual multimodal instruction tuning dataset across 39 languages. 🗂️ With 40% English instructions and 60% multilingual instructions, it spans various domains, including 1M culturally-relevant images sourced from LAION-Multi. 🎨
🏆 PangeaBench: A comprehensive evaluation benchmark featuring 14 datasets in 47 languages. Evaluation can be tricky, so we carefully curated existing benchmarks and introduced two new datasets: xChatBench (human-annotated wild queries with fine-grained evaluation criteria) and xMMMU (a meticulously machine-translated version of MMMU).
Check out more details: https://x.com/xiangyue96/status/1848753709787795679
🚀 Introducing Pangea: A Fully Open Multilingual Multimodal LLM supporting 39 languages! 🌐✨
https://neulab.github.io/Pangea/
https://arxiv.org/pdf/2410.16153
The Pangea family includes three major components:
🔥 Pangea-7B: A state-of-the-art multilingual multimodal LLM capable of 39 languages! Not only does it excel in multilingual scenarios, but it also matches or surpasses English-centric models like Llama 3.2, Molmo, and LlavaOneVision in English performance.
📝 PangeaIns: A 6M multilingual multimodal instruction tuning dataset across 39 languages. 🗂️ With 40% English instructions and 60% multilingual instructions, it spans various domains, including 1M culturally-relevant images sourced from LAION-Multi. 🎨
🏆 PangeaBench: A comprehensive evaluation benchmark featuring 14 datasets in 47 languages. Evaluation can be tricky, so we carefully curated existing benchmarks and introduced two new datasets: xChatBench (human-annotated wild queries with fine-grained evaluation criteria) and xMMMU (a meticulously machine-translated version of MMMU).
Check out more details: https://x.com/xiangyue96/status/1848753709787795679
reacted to
malhajar's
post with 🔥
26 days ago
Post
3727
🇫🇷 Lancement officiel de l'OpenLLM French Leaderboard : initiative open-source pour référencer l’évaluation des LLMs francophones
Après beaucoup d’efforts et de sueurs avec Alexandre Lavallee, nous sommes ravis d’annoncer que le OpenLLMFrenchLeaderboard est en ligne sur Hugging Face (space url: le-leadboard/OpenLLMFrenchLeaderboard) la toute première plateforme dédiée à l’évaluation des grands modèles de langage (LLM) en français. 🇫🇷✨
Ce projet de longue haleine est avant tout une œuvre de passion mais surtout une nécessité absolue. Il devient urgent et vital d'oeuvrer à plus de transparence dans ce domaine stratégique des LLM dits multilingues. La première pièce à l'édifice est donc la mise en place d'une évaluation systématique et systémique des modèles actuels et futurs.
Votre modèle IA français est-il prêt à se démarquer ? Soumettez le dans notre espace, et voyez comment vous vous comparez par rapport aux autres modèles.
❓ Comment ça marche :
Soumettez votre LLM français pour évaluation, et nous le testerons sur des benchmarks de référence spécifiquement adaptés pour la langue française — notre suite de benchmarks comprend :
- BBH-fr : Raisonnement complexe
- IFEval-fr : Suivi d'instructions
- GPQA-fr : Connaissances avancées
- MUSR-fr : Raisonnement narratif
- MATH_LVL5-fr : Capacités mathématiques
- MMMLU-fr : Compréhension multitâche
Le processus est encore manuel, mais nous travaillons sur son automatisation, avec le soutien de la communauté Hugging Face.
@clem , on se prépare pour une mise à niveau de l’espace ? 😏👀
Ce n'est pas qu'une question de chiffres—il s'agit de créer une IA qui reflète vraiment notre langue, notre culture et nos valeurs. OpenLLMFrenchLeaderboard est notre contribution personnelle pour façonner l'avenir des LLM en France.
Après beaucoup d’efforts et de sueurs avec Alexandre Lavallee, nous sommes ravis d’annoncer que le OpenLLMFrenchLeaderboard est en ligne sur Hugging Face (space url: le-leadboard/OpenLLMFrenchLeaderboard) la toute première plateforme dédiée à l’évaluation des grands modèles de langage (LLM) en français. 🇫🇷✨
Ce projet de longue haleine est avant tout une œuvre de passion mais surtout une nécessité absolue. Il devient urgent et vital d'oeuvrer à plus de transparence dans ce domaine stratégique des LLM dits multilingues. La première pièce à l'édifice est donc la mise en place d'une évaluation systématique et systémique des modèles actuels et futurs.
Votre modèle IA français est-il prêt à se démarquer ? Soumettez le dans notre espace, et voyez comment vous vous comparez par rapport aux autres modèles.
❓ Comment ça marche :
Soumettez votre LLM français pour évaluation, et nous le testerons sur des benchmarks de référence spécifiquement adaptés pour la langue française — notre suite de benchmarks comprend :
- BBH-fr : Raisonnement complexe
- IFEval-fr : Suivi d'instructions
- GPQA-fr : Connaissances avancées
- MUSR-fr : Raisonnement narratif
- MATH_LVL5-fr : Capacités mathématiques
- MMMLU-fr : Compréhension multitâche
Le processus est encore manuel, mais nous travaillons sur son automatisation, avec le soutien de la communauté Hugging Face.
@clem , on se prépare pour une mise à niveau de l’espace ? 😏👀
Ce n'est pas qu'une question de chiffres—il s'agit de créer une IA qui reflète vraiment notre langue, notre culture et nos valeurs. OpenLLMFrenchLeaderboard est notre contribution personnelle pour façonner l'avenir des LLM en France.
- 1 reply
reacted to
prithivMLmods's
post with 🔥🚀👍
26 days ago
Post
3928
I’m recently experimenting with the Flux-Ultra Realism and Real Anime LoRA models, using the Flux.1-dev model as the base. The model and its demo example are provided in the Flux LoRA DLC collections.📃
🥳Demo : 🔗 prithivMLmods/FLUX-LoRA-DLC
🥳Model:
- prithivMLmods/Canopus-LoRA-Flux-UltraRealism-2.0
- prithivMLmods/Flux-Dev-Real-Anime-LoRA
🥳For more details, please visit the README.md of the Flux LoRA DLC Space & prithivMLmods/lora-space-collections-6714b72e0d49e1c97fbd6a32
🥳Demo : 🔗 prithivMLmods/FLUX-LoRA-DLC
🥳Model:
- prithivMLmods/Canopus-LoRA-Flux-UltraRealism-2.0
- prithivMLmods/Flux-Dev-Real-Anime-LoRA
🥳For more details, please visit the README.md of the Flux LoRA DLC Space & prithivMLmods/lora-space-collections-6714b72e0d49e1c97fbd6a32
- 1 reply
reacted to
abhishek's
post with 👍
26 days ago
posted
an
update
30 days ago
Post
2228
China is advancing rapidly in AI technology while maintaining a strong focus on governance 🇨🇳📑
We've collected key AI governance documents released since 2017 and will continue updating them in this organization on the hub 👉China LLMs on Hugging Face
✨ zh-ai-community/china-ai-policy-research
Any feedback is welcome🤗
We've collected key AI governance documents released since 2017 and will continue updating them in this organization on the hub 👉China LLMs on Hugging Face
✨ zh-ai-community/china-ai-policy-research
Any feedback is welcome🤗
reacted to
singhsidhukuldeep's
post with 👀
about 1 month ago
Post
2007
Just started going through the latest "State of AI Report 2024", and I cannot get over the predictions!
The report predicts major developments in AI over the next 12 months, including a $10B+ investment from a sovereign state into a large US AI lab, triggering national security scrutiny, and a viral app created by someone without coding skills.
It forecasts changes in data collection practices due to frontier labs facing trials, softer-than-expected EU AI Act implementations, and the rise of an open-source alternative to OpenAI GPT-4 outperforming in benchmarks.
NVIDIA’s dominance will remain largely unchallenged, investment in humanoid robots will decline, Apple’s on-device AI research will gain momentum, and a research paper by an AI scientist will be accepted at a major conference.
Lastly, a GenAI-based video game is expected to achieve breakout success.
Yet to go through all 200+ pages... will post summarized thoughts later.
The report predicts major developments in AI over the next 12 months, including a $10B+ investment from a sovereign state into a large US AI lab, triggering national security scrutiny, and a viral app created by someone without coding skills.
It forecasts changes in data collection practices due to frontier labs facing trials, softer-than-expected EU AI Act implementations, and the rise of an open-source alternative to OpenAI GPT-4 outperforming in benchmarks.
NVIDIA’s dominance will remain largely unchallenged, investment in humanoid robots will decline, Apple’s on-device AI research will gain momentum, and a research paper by an AI scientist will be accepted at a major conference.
Lastly, a GenAI-based video game is expected to achieve breakout success.
Yet to go through all 200+ pages... will post summarized thoughts later.
- 2 replies
reacted to
clem's
post with 🚀😎❤️
about 1 month ago
Post
4139
Open-source AI creates healthy competition in a field where natural tendencies lead to extreme concentration of power. Imagine a world where only one or two companies could build software. This is the biggest risk and ethical challenge of them all IMO. Let's fight this!
- 3 replies
reacted to
thughost's
post with 🔥
about 1 month ago
Post
691
We've open-sourced the code and models for Self-Play Preference Optimization (SPPO)! 🚀🚀🚀
🤗paper: Self-Play Preference Optimization for Language Model Alignment (2405.00675)
⭐ code: https://github.com/uclaml/SPPO
🤗models: UCLA-AGI/sppo-6635fdd844f2b2e4a94d0b9a
🤗paper: Self-Play Preference Optimization for Language Model Alignment (2405.00675)
⭐ code: https://github.com/uclaml/SPPO
🤗models: UCLA-AGI/sppo-6635fdd844f2b2e4a94d0b9a