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🔥 HuggingFace's Transformers: State-of-the-art Natural Language Processing
📅 Published on Oct 9, 2019
🔗 Links:
• GitHub: https://github.com/huggingface
• arXiv: https://arxiv.org/abs/1910.03771
• PDF: https://arxiv.org/pdf/1910.03771
• Project Page: https://huggingface.co
🤖 Models citing this paper:
• https://huggingface.co/PJMixers-Images/Florence-2-base-Castollux-v0.5
• https://huggingface.co/Ian332/Helper_Bob
• https://huggingface.co/PJMixers-Images/Florence-2-base-Castollux-v0.2
🚀 Spaces citing this paper:
• https://huggingface.co/spaces/dpratapa/bio-seq-lm-explorer
• https://huggingface.co/spaces/itchybeetle3/img_caption_generation
• https://huggingface.co/spaces/PJMixers-Images/Florence-2-base-Castollux-v0.5
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📢 By: https://xn--r1a.website/PaperNexus
#NaturalLanguageProcessing #TransformerArchitectures #PretrainedModels #StateOfTheArtAI #MachineLearningLibrary
💡 The paper discusses the Transformers library, an open source collection of state of the art Transformer architectures and pretrained models for natural language processing tasks. The library aims to make recent advances in natural language processing accessible to the wider machine learning community. The problem addressed is the difficulty in utilizing recent advances in model architecture and pretraining for natural language processing tasks. The method used is the creation of a unified API that provides access to a range of carefully engineered state of the art Transformer architectures, along with a curated collection of pretrained models. The library is designed to be extensible for researchers, simple for practitioners, and fast and robust for industrial deployments. The results are a library that provides a simple and unified way to access and utilize state of the art natural language processing models, making it easier for researchers and practitioners to build and deploy effective natural language processing systems. The library is available for use and contribution by the community, with the goal of driving further advances in natural language processing.
📅 Published on Oct 9, 2019
🔗 Links:
• GitHub: https://github.com/huggingface
• arXiv: https://arxiv.org/abs/1910.03771
• PDF: https://arxiv.org/pdf/1910.03771
• Project Page: https://huggingface.co
🤖 Models citing this paper:
• https://huggingface.co/PJMixers-Images/Florence-2-base-Castollux-v0.5
• https://huggingface.co/Ian332/Helper_Bob
• https://huggingface.co/PJMixers-Images/Florence-2-base-Castollux-v0.2
🚀 Spaces citing this paper:
• https://huggingface.co/spaces/dpratapa/bio-seq-lm-explorer
• https://huggingface.co/spaces/itchybeetle3/img_caption_generation
• https://huggingface.co/spaces/PJMixers-Images/Florence-2-base-Castollux-v0.5
━━━━━━━━━━━━━━━━━━━━━━━━
📢 By: https://xn--r1a.website/PaperNexus
#NaturalLanguageProcessing #TransformerArchitectures #PretrainedModels #StateOfTheArtAI #MachineLearningLibrary
GitHub
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