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Sami Halawa PRO

luigi12345

https://samihalawa.pages.dev

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posted an update about 3 hours ago

🚀 Meta’s Llama 4 Models Now on Hugging Face! Meta has released Llama 4 Scout and Llama 4 Maverick, now available on Hugging Face: • Llama 4 Scout: 17B active parameters, 16-expert Mixture of Experts (MoE) architecture, 10M token context window, fits on a single H100 GPU. • Llama 4 Maverick: 17B active parameters, 128-expert MoE architecture, 1M token context window, optimized for DGX H100 systems. 🔥 Key Features: • Native Multimodality: Seamlessly processes text and images. • Extended Context Window: Up to 10 million tokens for handling extensive inputs. • Multilingual Support: Trained on 200 languages, with fine-tuning support for 12, including Arabic, Spanish, and German. 🛠️ Access and Integration: • Model Checkpoints: Available under the meta-llama organization on the Hugging Face Hub. • Transformers Compatibility: Fully supported in transformers v4.51.0 for easy loading and fine-tuning. • Efficient Deployment: Supports tensor-parallelism and automatic device mapping. These models offer developers enhanced capabilities for building sophisticated, multimodal AI applications.

posted an update 8 days ago

🚀 DEEPSEEK R1… Replicated! 🧠✨ All powered by just ONE system prompt. Try it. Compare it. See for yourself. 👀 🔥 Even better than the original — with richer, more insightful replies. 🎯 No gimmicks. Just pure AI performance. [](https://chatgpt.com/g/g-67e5e1e379e88191873752b60f518a14-deepseek-r1-thinking) PROMPT IN THE COMMENTS

updated a Space 8 days ago

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🚀 Meta’s Llama 4 Models Now on Hugging Face!

Meta has released Llama 4 Scout and Llama 4 Maverick, now available on Hugging Face:
• Llama 4 Scout: 17B active parameters, 16-expert Mixture of Experts (MoE) architecture, 10M token context window, fits on a single H100 GPU.
• Llama 4 Maverick: 17B active parameters, 128-expert MoE architecture, 1M token context window, optimized for DGX H100 systems.

🔥 Key Features:
• Native Multimodality: Seamlessly processes text and images.
• Extended Context Window: Up to 10 million tokens for handling extensive inputs.
• Multilingual Support: Trained on 200 languages, with fine-tuning support for 12, including Arabic, Spanish, and German.

🛠️ Access and Integration:
• Model Checkpoints: Available under the meta-llama organization on the Hugging Face Hub.
• Transformers Compatibility: Fully supported in transformers v4.51.0 for easy loading and fine-tuning.
• Efficient Deployment: Supports tensor-parallelism and automatic device mapping.

These models offer developers enhanced capabilities for building sophisticated, multimodal AI applications.

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