kaiiddo

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reacted to nyuuzyou's post with 🔥 5 days ago

🖼️ Clker.com SVG Images Dataset - https://huggingface.co/datasets/nyuuzyou/clker-svg Collection of 274,859 Public Domain Scalable Vector Graphics (SVG) clipart images featuring: - Sourced from Clker.com, a platform for user-shared vector clipart - Includes metadata: unique ID, title, tags, and original download URL - Contains complete SVG XML content for direct use or processing - All images explicitly released into the public domain under CC0 license - Organized in a single train split with 274,859 entries With nearly 275,000 public domain vector images, this represents one of the largest freely available SVG clipart collections on Hugging Face. While smaller than the SVGFind dataset, its public domain licensing makes it particularly valuable for commercial and unrestricted use cases without attribution requirements.

reacted to openfree's post with 🔥 5 days ago

🚀 Introducing Phi-4-reasoning-plus: Powerful 14B Reasoning Model by Microsoft! https://huggingface.co/spaces/VIDraft/phi-4-reasoning-plus 🌟 Key Highlights Compact Size (14B parameters): Efficient for use in environments with limited computing resources, yet powerful in performance. Extended Context (32k tokens): Capable of handling lengthy and complex input sequences. Enhanced Reasoning: Excels at multi-step reasoning, particularly in mathematics, science, and coding challenges. Chain-of-Thought Methodology: Provides a detailed reasoning process, followed by concise, accurate summaries. 🏅 Benchmark Achievements Despite its smaller size, Phi-4-reasoning-plus has delivered impressive results, often surpassing significantly larger models: Mathematical Reasoning (AIME 2025): Achieved an accuracy of 78%, significantly outperforming larger models like DeepSeek-R1 Distilled (51.5%) and Claude-3.7 Sonnet (58.7%). Olympiad-level Math (OmniMath): Strong performance with an accuracy of 81.9%, surpassing DeepSeek-R1 Distilled's 63.4%. Graduate-Level Science Questions (GPQA-Diamond): Delivered competitive performance at 68.9%, close to larger models and demonstrating its capabilities in advanced scientific reasoning. Coding Challenges (LiveCodeBench): Scored 53.1%, reflecting strong performance among smaller models, though slightly behind specialized coding-focused models. 🛡️ Safety and Robustness Comprehensive safety evaluation completed through Microsoft's independent AI Red Team assessments. High standards of alignment and responsible AI compliance validated through extensive adversarial testing. 🎯 Recommended Applications Phi-4-reasoning-plus is especially suitable for: Systems with limited computational resources. Latency-sensitive applications requiring quick yet accurate responses. 📜 License Freely available under the MIT License for broad accessibility and flexible integration into your projects.

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reacted to nyuuzyou's post with 🔥 5 days ago

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1415

🖼️ Clker.com SVG Images Dataset - nyuuzyou/clker-svg

Collection of 274,859 Public Domain Scalable Vector Graphics (SVG) clipart images featuring:
- Sourced from Clker.com, a platform for user-shared vector clipart
- Includes metadata: unique ID, title, tags, and original download URL
- Contains complete SVG XML content for direct use or processing
- All images explicitly released into the public domain under CC0 license
- Organized in a single train split with 274,859 entries

With nearly 275,000 public domain vector images, this represents one of the largest freely available SVG clipart collections on Hugging Face. While smaller than the SVGFind dataset, its public domain licensing makes it particularly valuable for commercial and unrestricted use cases without attribution requirements.

reacted to openfree's post with 🔥 5 days ago

Post

2473

🚀 Introducing Phi-4-reasoning-plus: Powerful 14B Reasoning Model by Microsoft!

VIDraft/phi-4-reasoning-plus

🌟 Key Highlights
Compact Size (14B parameters): Efficient for use in environments with limited computing resources, yet powerful in performance.

Extended Context (32k tokens): Capable of handling lengthy and complex input sequences.

Enhanced Reasoning: Excels at multi-step reasoning, particularly in mathematics, science, and coding challenges.

Chain-of-Thought Methodology: Provides a detailed reasoning process, followed by concise, accurate summaries.

🏅 Benchmark Achievements
Despite its smaller size, Phi-4-reasoning-plus has delivered impressive results, often surpassing significantly larger models:

Mathematical Reasoning (AIME 2025): Achieved an accuracy of 78%, significantly outperforming larger models like DeepSeek-R1 Distilled (51.5%) and Claude-3.7 Sonnet (58.7%).

Olympiad-level Math (OmniMath): Strong performance with an accuracy of 81.9%, surpassing DeepSeek-R1 Distilled's 63.4%.

Graduate-Level Science Questions (GPQA-Diamond): Delivered competitive performance at 68.9%, close to larger models and demonstrating its capabilities in advanced scientific reasoning.

Coding Challenges (LiveCodeBench): Scored 53.1%, reflecting strong performance among smaller models, though slightly behind specialized coding-focused models.

🛡️ Safety and Robustness
Comprehensive safety evaluation completed through Microsoft's independent AI Red Team assessments.

High standards of alignment and responsible AI compliance validated through extensive adversarial testing.

🎯 Recommended Applications
Phi-4-reasoning-plus is especially suitable for:
Systems with limited computational resources.
Latency-sensitive applications requiring quick yet accurate responses.

📜 License
Freely available under the MIT License for broad accessibility and flexible integration into your projects.