Memory efficient MAML using gradient checkpointing
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Dec 30, 2019 - Jupyter Notebook
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gradient-checkpointing
Here are 9 public repositories matching this topic...
Simple gradient checkpointing for eager mode execution
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Dec 12, 2020 - Python
Python package for rematerialization-aware gradient checkpointing
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Oct 31, 2023 - Python
Python library for memory-constrained activation checkpoint optimization, recomputation scheduling, and GPU training performance analysis.
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Sep 2, 2026 - TypeScript
Zero-memory, multi-core-CPU local AI training for ordinary laptops.
python machine-learning multiprocessing numpy python3 autograd neural-networks out-of-core low-memory no-gpu ai-training gradient-checkpointing local-ai 8bit-optimizer cpu-only
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Oct 1, 2026 - Python
End-to-end fine-tuning of Hugging Face models using LoRA, QLoRA, quantization, and PEFT techniques. Optimized for low-memory with efficient model deployment
nlp machine-learning natural-language-processing deep-learning transformers pytorch lora quantization model-training fine-tuning peft gpu-optimization huggingface gradient-checkpointing huggingface-datasets qlora bitsandbytes parameter-efficient-fine-tuning low-memory-training fp16-training
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Dec 27, 2025 - Jupyter Notebook
Gradient checkpointing and VRAM auto-tuning for spiking neural network training. O(sqrt(T)) activation memory with bit-identical gradients.
python deep-learning pytorch gpu-memory spiking-neural-networks neuromorphic memory-optimization gradient-checkpointing bptt snntorch
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Aug 27, 2026 - Python
Fine-tune NVIDIA Isaac GR00T N1.7 (3B VLA) on a single 24 GB RTX 4090 without root: patches, install script, MuJoCo evaluation, open datasets, 1800 evaluated attempts as JSON
robotics reproducible-research nvidia imitation-learning vla robot-learning mujoco fine-tuning gradient-checkpointing embodied-ai bitsandbytes vision-language-action lerobot low-vram consumer-gpu gr00t rtx-4090 so-arm100 so-101 isaac-gr00t
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Sep 8, 2026 - Python
Classify documents longer than your transformer's context window: overlapping windows, cross-window aggregation (max / mean / top-k / log-mean-exp), and window-level gradient checkpointing that cuts training memory. Encoder-agnostic and task-agnostic, with measured speed and accuracy trade-offs.
nlp machine-learning text-classification transformers pytorch document-classification bert sliding-window multiple-instance-learning huggingface gradient-checkpointing long-document
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Sep 23, 2026 - Python
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