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At @fal , we've achieved 16 times higher throughput on Qwen3.6 for a use-case that required high interactivity per user using DSpark on SGLang. But why did we need it? And how did we achieve it?IntroText-to-image models like Ideogram V4 can generate stunning,
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Release v5.13.0 · huggingface/transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - Release Patch release v5.12.1 · huggingface/transformers
Go ahead and axolotl questions. Contribute to axolotl-ai-cloud/axolotl development by creating an account on GitHub.
Go ahead and axolotl questions. Contribute to axolotl-ai-cloud/axolotl development by creating an account on GitHub.
A 2025 review of large language models, from DeepSeek R1 and RLVR to inference-time scaling, benchmarks, architectures, and predictions for 2026.
How LoRA matches full training performance more broadly than expected.
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch. - Release Diffusers 0.35.0: Qwen Image pipelines, Flux Kontext, Wan 2.2, and more · huggingface/diffusers
Learn how to fine-tune large language models for specific needs. A practical guide covering techniques, tools, and best practices.
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch. - Release Diffusers 0.34.0: New Image and Video Models, Better torch.compile Support, and more · huggingface/diffusers
NLP research has undergone a paradigm shift over the last year. A range of large language models (LLMs) has validated the unreasonable effectiveness of scale1.
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