AI · alternatives · 2026
24 alternatives to Keep your PyTorch model in VRAM by hot swapping code
Pytorch script hot swap: Change code without unloading your LLM from VRAM - valine/training-hot-swap
This tool helps developers manage PyTorch model memory by automatically swapping code in and out of VRAM during execution. It's designed for machine learning engineers working with large models who need to optimize GPU… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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PMB▲211PMB gives Claude Code, Cursor, Codex and Zed a real memory. Decisions, lessons and facts in one SQLite file on your disk. Offline, no API keys, no cloud.
Jun 2026 · pmbai.dev · its alternatives →
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We're excited to announce that we've open-sourced LeanRL, a lightweight PyTorch reinforcement learning library that provides recipes for fast RL training using torch.compile and CUDA graphs. By leveraging these tools, we've achieved significant speed-ups compared to the original CleanRL implementations - up to 6x faster! Reinforcement learning is notoriously CPU-bound due to the high frequency of small CPU operations. PyTorch's powerful compiler can help alleviate these issues, but comes with its own costs. LeanRL addresses this challenge by providing simple recipes to accelerate your…
2024 · github.com · its alternatives →
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Hi everyone, I'm kinda involved in some retrogaming and with some experiments I ran into the following question: "It would be possible to run transformer models bypassing the cpu/ram, connecting the gpu to the nvme?" This is the result of that question itself and some weekend vibecoding (it has the linked library repository in the readme as well), it seems to work, even on consumer gpus, it should work better on professional ones tho
Feb 2026 · github.com · its alternatives →
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Forge Agent▲113Swarm Agents That Turn Slow PyTorch Into Fast GPU Kernels
Jan 2026 · rightnowai.co · its alternatives →
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2023 · vram.asmirnov.xyz · its alternatives →
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Keep Python on your laptop. Run PyTorch operations and hold tensors on a remote GPU, including from a Mac with no CUDA installation. - ymcrcat/rgpu
14d ago · github.com · its alternatives →
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Weights & Biases▲110Developer tools for deep learning & machine learning
2019 · wandb.ai · its alternatives →
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Stop wasting tokens and re-explaining your project every session. Recall gives Claude Code durable memory — entirely offline. - raiyanyahya/recall
Jun 2026 · github.com · its alternatives →
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I got tired of Claude Code forgetting all my context every time I open a new session: set-up decisions, how I like my margins, decision history. etc. We built a shared memory layer you can drop in as a Claude Code Skill. It’s basically a tiny memory DB with recall that remembers your sessions. Not magic. Not AGI. Just state. Install in Claude Code: /plugin marketplace add https://github.com/mutable-state-inc/ensue-skill /plugin install ensue-memory # restart Claude Code What it does: (1) persists context between sessions (2) semantic & temportal search (not just…
Dec 2025 · github.com · its alternatives →
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Change Python code while it's running without losing state - julvo/reloading
2019 · github.com · its alternatives →
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Vibe profile your ML models to get max performance.
2025 · github.com · its alternatives →
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Hi HN, Over the past few months, I've been building `dsc`, a tensor library from scratch in C++/CUDA. My main focus has been on getting the basics right, prioritizing a clean API, simplicity, and clear observability for running small LLMs locally. The key features are: - C++ core with CUDA support written from scratch. - A familiar, PyTorch-like Python API. - Runs real models: it's complete enough to load a model like Qwen from HuggingFace and run inference on both CUDA and CPU with a single line change[1]. - Simple, built-in observability for both Python and C++. Next on the roadmap is…
2025 · github.com · its alternatives →
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Perform data science on data that remains in someone else's server - OpenMined/PySyft
2018 · github.com · its alternatives →
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We built RapidFire AI, an open-source Python tool to speed up LLM fine-tuning and post-training with a powerful level of control not found in most tools: Stop, resume, clone-modify and warm-start configs on the fly—so you can branch experiments while they’re running instead of starting from scratch or running one after another. - Works within your OSS stack: PyTorch, HuggingFace TRL/PEFT), MLflow. - Hyperparallel search: launch as many configs as you want together, even on a single GPU - Dynamic real-time control: stop laggards, resume them later to revisit, branch promising configs in…
2025 · github.com · its alternatives →
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I forked a PyTorch DeepDream implementation and added video support with temporal consistency. It produces smooth DeepDream videos with minimal flickering, and is highly flexible including many parameters and supports multiple pretrained image classifiers including GoogLeNet. Check out the repo for sample videos! Features: - Optical flow warps previous hallucinations into the current frame - Occlusion masking prevents ghosting and hallucination transfer when objects move - Advanced parameters (layers, octaves, iterations) still work - Works on GPU, CPU, and Apple Silicon
Jan 2026 · github.com · its alternatives →
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This is a low-level opensource library I developed for my own use and decided to share, as it makes it possible to process large checkpoints of neural networks without renting high-RAM instances, on a regular PC. It replaces torch.load() with a custom function that produces a dictionary that materializes tensors on the fly. Compared to other solutions it doesn't require sharding or re-encoding checkpoints and uses them completely as-is. It is a foundation to make it possible to run inference and compress language models and other large models one layer at a time - in principle, even one…
2023 · github.com · its alternatives →
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Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc. - CaviraOSS/LongMemory
Dec 2025 · github.com · its alternatives →
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I integrated a remote GPU execution backend into PyTorch through the same system that custom hardware accelerators get integrated into PyTorch. You can create a remote machine and obtain its CUDA device whenever you want to create or move tensors onto the remote GPU. machine = mycelya_torch.RemoteMachine("modal", "A100") cuda_device = machine.device("cuda") x = torch.randn(1000, 1000, device=cuda_device) y = torch.randn(1000, 1000).to(cuda_device) I made it reasonably performant by having most operations dispatch asynchronously whenever possible. For cases where slow performance is…
2025 · github.com · its alternatives →
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Zero-Copy Context Bridging Gateway for Multi-Agent GPU Inference. Bypasses the expensive prefill phase by dynamically stitching KV Caches at the memory level using PagedAttention. Cuts TTFT latency by up to 25x and saves 40%+ VRAM for collaborative LLM workflows. - DaqulaLin/MemStitch
Jul 2026 · github.com · its alternatives →
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We needed a side project to give agentic coding a try, and created tensorspy.com together with Junie and ChatGPT 5.2. Tensor Spy lets you quickly inspect the contents of numpy & pytorch tensors locally (your tensors are not uploaded to any servers). This is useful to validate your deep learning data pipelines, to check which layers in your diverging model are actually going haywire, and just because it's kind of cool & a lot more convenient for one-off inspections than loading things up in python. If you work with diffusion models, inspecting the latent space can be quite informative: you…
Mar 2026 · tensorspy.com · its alternatives →
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Today I am excited to release pytorch-block-sparse: a *drop-in* replacement of @PyTorch Linear with GPU-efficient sparsity: 75% sparsity➡️4x less memory + 2x the speed! Code & tutorials to use to train your own sparse models: https://t.co/HMO11zWAjk
2020 · twitter.com · its alternatives →
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