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🔄 Data last refreshed 1 month ago
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Make a deal with PyTorch
👋 Unclaimed listing — auto-generated from public data; rates are estimates, not set by the creator. 🔒 Paid proposals held safely in escrow — released only when the work's approved.
This is an unclaimed, auto-generated listing. It was built only from PyTorch’s publicly available X information. PyTorch has not claimed, verified, or endorsed it, and is not affiliated with, sponsored by, or a partner of SocialDB — no partnership or endorsement is implied, and any prices shown are estimates, not set by the creator.
Followers
511K
Posts
3.6K
Following
95
Account age
10 yrs
💰 Suggested sponsorship rate
$2.9K – $4.7K / sponsored post
Estimated from audience size & typical reach — every deal is negotiable and held in SocialDB escrow.
🎁 Free analysisfor PyTorch
Known for
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
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
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
Recent posts · views
Mar 15latest
198.6K
Avg views / post
156.4K–484.6K
Typical post (views)
38.9%
Reach vs followers
73/100
Consistent reach
Sep 2016
On X since
Half of recent posts land between 156.4K and 484.6K views (median 326.7K) — a dependable floor a sponsored post can count on.
🔥 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
5.4K×
Follows 95 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 ↗
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…
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!
…
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. 🔥
▶
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
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
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
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
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…
▶
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.
▶
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…
▶
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
💡 Facts
🗓️Joined X in 2016 — 10 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.
🕵️ Fake follower check
Estimated69/100
Good
Credibility score
85%
Real
Real audience
Low
Fake-follower risk
High
Data confidence
- Est. 85% real, active audience · Low fake-follower risk.
- Engagement (~0.4× of followers engage each post) is around typical for X.
- Organic base — far more followers than accounts it follows.
- Verified account.
- Established account (10+ years old).
- 0.44% engagement — below the ~2.2% 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
📸 Gallery
🔀 Audience overlap
EstimatedEstimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.
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16%
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15%
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Followers
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How many followers does PyTorch have?
PyTorch has 511,001 followers on X.
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