✨PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel
📝 Summary:
PyTorch FSDP is an industry-grade solution for efficient and scalable large model training. It enables significantly larger models with near-linear TFLOPS scalability, making advanced capabilities more accessible.
🔹 Publication Date: Published on Apr 21, 2023
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2304.11277
• PDF: https://arxiv.org/pdf/2304.11277
• Github: https://github.com/pytorch/pytorch/blob/main/torch/distributed/fsdp/fully_sharded_data_parallel.py
🔹 Models citing this paper:
• https://huggingface.co/databricks/dbrx-instruct
• https://huggingface.co/databricks/dbrx-base
• https://huggingface.co/Undi95/dbrx-base
✨ Spaces citing this paper:
• https://huggingface.co/spaces/nanotron/ultrascale-playbook
• https://huggingface.co/spaces/Ki-Seki/ultrascale-playbook-zh-cn
• https://huggingface.co/spaces/Gantrol/ultrascale-playbook-zh-cn
==================================
For more data science resources:
✓ https://t.me/DataScienceT
#PyTorch #FSDP #DeepLearning #DistributedTraining #LargeModels
📝 Summary:
PyTorch FSDP is an industry-grade solution for efficient and scalable large model training. It enables significantly larger models with near-linear TFLOPS scalability, making advanced capabilities more accessible.
🔹 Publication Date: Published on Apr 21, 2023
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2304.11277
• PDF: https://arxiv.org/pdf/2304.11277
• Github: https://github.com/pytorch/pytorch/blob/main/torch/distributed/fsdp/fully_sharded_data_parallel.py
🔹 Models citing this paper:
• https://huggingface.co/databricks/dbrx-instruct
• https://huggingface.co/databricks/dbrx-base
• https://huggingface.co/Undi95/dbrx-base
✨ Spaces citing this paper:
• https://huggingface.co/spaces/nanotron/ultrascale-playbook
• https://huggingface.co/spaces/Ki-Seki/ultrascale-playbook-zh-cn
• https://huggingface.co/spaces/Gantrol/ultrascale-playbook-zh-cn
==================================
For more data science resources:
✓ https://t.me/DataScienceT
#PyTorch #FSDP #DeepLearning #DistributedTraining #LargeModels
arXiv.org
PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel
It is widely acknowledged that large models have the potential to deliver superior performance across a broad range of domains. Despite the remarkable progress made in the field of machine...
✨Dynamic Large Concept Models: Latent Reasoning in an Adaptive Semantic Space
📝 Summary:
DLCM shifts computation from individual tokens to a compressed concept space, enabling more efficient reasoning. This hierarchical approach learns semantic boundaries end-to-end and improves performance on benchmarks by reallocating compute.
🔹 Publication Date: Published on Dec 31, 2025
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.24617
• PDF: https://arxiv.org/pdf/2512.24617
==================================
For more data science resources:
✓ https://t.me/DataScienceT
#AI #MachineLearning #LargeModels #RepresentationLearning #EfficientAI
📝 Summary:
DLCM shifts computation from individual tokens to a compressed concept space, enabling more efficient reasoning. This hierarchical approach learns semantic boundaries end-to-end and improves performance on benchmarks by reallocating compute.
🔹 Publication Date: Published on Dec 31, 2025
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.24617
• PDF: https://arxiv.org/pdf/2512.24617
==================================
For more data science resources:
✓ https://t.me/DataScienceT
#AI #MachineLearning #LargeModels #RepresentationLearning #EfficientAI