PyTorch✓

X @pytorch

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🔒 Paid proposals held safely in escrow — released only when the work's approved.

Followers

504.1K

Posts

3.4K

Following

Account age

9 yrs

🧰 Free analysis for PyTorch

🕵️ Fake follower check 📊 Engagement rate 💰 What they charge

Known for

We’re excited to announce the release of PyTorch 2.0!

This version includes:
⚙️ 100% backward compatible
📦 Out of the box performance
📶 Significant speed improvements

Learn more 👇
https://t.co/8vV61atP6E

484.6K views We’re excited to announce the release of PyTorch 2.0! This version includes: ⚙️ 100% backward compatible 📦 Out of the box performance 📶 Significant speed improvements Learn more 👇 https://t.co/8vV61atP6E

Inside the Matrix: Use 3D to visualize matrix multiplication expressions, attention heads with real weights, and more. ⚡

Read our latest post on visualizing matrix multiplication, attention and beyond: https://t.co/8G2rAAccv8

326.7K views Inside the Matrix: Use 3D to visualize matrix multiplication expressions, attention heads with real weights, and more. ⚡ Read our latest post on visualizing matrix multiplication, attention and beyond: https://t.co/8G2rAAccv8

PyTorch 2.9 is now available, introducing key updates to performance, portability, and the developer experience.

This release includes a stable libtorch ABI for C++/CUDA extensions, symmetric memory for multi-GPU kernels, expanded wheel support to include ROCm, XPU, and CUDA 13,

123.9K views PyTorch 2.9 is now available, introducing key updates to performance, portability, and the developer experience. This release includes a stable libtorch ABI for C++/CUDA extensions, symmetric memory for multi-GPU kernels, expanded wheel support to include ROCm, XPU, and CUDA 13,

📊 Post performance

198.6K

Avg views / post

39.4%

Reach vs followers

Sep 2016

On X since

🔥 Top post: We are announcing that PyTorch will stop publishing Anaconda pac · 681.2K views

📊 Activity & format

Posting cadence

0.05 / week

A lower-frequency account — each post lands with more weight.

Content mix

Mostly images

Recent: 5 video · 8 image · 5 text.

Follower / following

5.8K×

Follows 87 back. A strong ratio — an audience that follows them, not a follow-for-follow network.

Verification

✓ X Premium

A paid X Premium (Blue) verified account.

Recent posts

View on X ↗

🔥 Top post We are announcing that PyTorch will stop publishing Anaconda packages on PyTorch’s official anaconda channels. For more information, please refer to the following post on dev-discuss: 681.2K❤ 1.4K🔁 354

PyTorch 2.9 is now available, introducing key updates to performance, portability, and the developer experience. This release includes a stable libtorch ABI for C++/CUDA extensions, symmetric memory for multi-GPU kernels, expanded wheel s… 123.9K❤ 1.4K🔁 200 Announcing the alpha release of torchtune! torchtune is a PyTorch-native library for fine-tuning LLMs. It combines hackable memory-efficient fine-tuning recipes with integrations into your favorite tools. Get started fine-tuning today! … 156.4K❤ 1.4K🔁 302 10x performance on LLaMa 7B, all in native PyTorch. No C++ needed. Check out our second blog post in a series on Accelerating Generative AI using Native PyTorch. 🔥 198.6K❤ 1.5K🔁 266

▶ Inside the Matrix: Use 3D to visualize matrix multiplication expressions, attention heads with real weights, and more. ⚡ Read our latest post on visualizing matrix multiplication, attention and beyond: https://t.co/8G2rAAccv8 326.7K❤ 1.9K🔁 390

We’re excited to announce the release of PyTorch 2.0! This version includes: ⚙️ 100% backward compatible 📦 Out of the box performance 📶 Significant speed improvements Learn more 👇 https://t.co/8vV61atP6E 484.6K❤ 2K🔁 604

We just introduced PyTorch 2.0 at the #PyTorchConference, introducing torch.compile! Available in the nightlies today, stable release Early March 2023. Read the full post: https://t.co/DFO0HojkMt 🧵below! 1/5 ❤ 1.7K🔁 512

We’re excited to announce support for GPU-accelerated PyTorch training on Mac! Now you can take advantage of Apple silicon GPUs to perform ML workflows like prototyping and fine-tuning. Learn more: https://t.co/8VmtnhfrZy ❤ 3.1K🔁 713

Today marks 5 years since the public release of PyTorch! We didn't expect to come this far, but here we're🙂- 2K Contributors, 90K Projects, 3.9M lines of "import torch" on GitHub. More importantly, we're still receiving lots of love and ha… ❤ 3.2K🔁 482

▶ Want to make your inference code in PyTorch run faster? Here’s a quick thread on doing exactly that. 1. Replace https://t.co/OG6jlroK1O_grad() with the ✨torch.inference_mode()✨ context manager. ❤ 1.7K🔁 360

▶ Introducing torch.profiler! New PyTorch Profiler collects both GPU and framework related info, correlates them, performs automatic detection of bottlenecks in the model, generates recommendations on how to resolve these bottlenecks, and vi… ❤ 1.3K🔁 324

▶ We're excited to release the torch.fft module in PyTorch 1.8. This module implements the same functions as NumPy’s np.fft module, but with support for accelerators, like GPUs, and autograd. Learn more 👉 https://t.co/Q8159dyltF ❤ 1.5K🔁 273

💡 Facts

🗓️Joined X in 2016 — 9 years ago.

👁️Averages 198.6K views per post.

📤Posts about 0.1× per week.

💬0.44% engagement rate.

🏅Earned the 100K Followers for passing 100K followers.

🛡️ Audience credibility

46/100

Fair Credibility score

69%

Mixed Real audience

Medium Fake-follower risk

High Data confidence

Est. 69% real, active audience · Medium fake-follower risk.
Low engagement (~0.4× of followers engage each post) — a sign of an inflated or inactive audience.
Organic base — far more followers than accounts it follows.
Verified account.
Established account (9+ years old).
0.44% engagement — below the ~14.4% typical for this size.

Heuristic estimate from engagement, follower ratios, account age & growth — a screening signal, not a guarantee.

About

Tensors and neural networks in Python with strong hardware acceleration. PyTorch is an open source project at the Linux Foundation. #PyTorchFoundation

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🔀 Audience overlap

Estimated

Estimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.

ThePrintIndia 17%

東山奈央オフィシャル 15%

Mark Rober 15%

Conservative Self-Owns 14%

BookMyShow 13%

TwitchBR 13%

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