neuron-explorer
Steering-first neuron explorer for Qwen3.5-4B: push every MLP neuron, keep every rollout, browse the results
Mia deploys and benchmarks open-weight AI models on NVIDIA DGX Sparks: recipes, honest comparisons with frontier models, personal installs and guides.
Developer toolsShell · PythonGitHub @MiaAI-LabOnlineOwner unconfirmed
Have you tried it? One tap is enough. No sign-in needed.
No updates detected yet. GitHub releases will appear here.
Owners of public repositories under a personal GitHub account can sign in to verify ownership and manage the introduction themselves. No administrator approval is needed.
Sign in, generate a verification file, and commit it to this repository’s default branch within 30 minutes. Files on other branches or forks do not count. Then check the file below to manage the project without administrator approval. Keep the file to retain your access.
If needed, you will go to sign-in. After signing in, return here and press your chosen verification button again.
Run /nomorevibe verify in your project folder to verify ownership and manage the introduction yourself.
Verify in one minuteAsk about other verification options
Qwen3.8 Flash Next on one DGX Spark (TensorFold)
Translation pending
Taken from the repository README
Loading the full README. The saved excerpt is shown below.
Qwen3.8 Flash Next on one DGX Spark (TensorFold)
Serve Qwen3.8 Flash Next from a single NVIDIA DGX Spark (GB10, 128 GB) through an OpenAI-compatible API, with
5 concurrent requests at the full 262,144-token context and image and video input. It runs
TensorFold v0.6.1 (17c73e1) in NVIDIA's PyTorch container, plus
patches/0002-flash-next-v061.patch (video input and many images on TensorFold's Flash Next vision, copy drafts,
SSD read-ahead, first token before the next draft).Read the full README ↗The full README is unavailable right now. Read it at the original link. The saved excerpt is shown below.
Qwen3.8 Flash Next on one DGX Spark (TensorFold)
Serve Qwen3.8 Flash Next from a single NVIDIA DGX Spark (GB10, 128 GB) through an OpenAI-compatible API, with
5 concurrent requests at the full 262,144-token context and image and video input. It runs
TensorFold v0.6.1 (17c73e1) in NVIDIA's PyTorch container, plus
patches/0002-flash-next-v061.patch (video input and many images on TensorFold's Flash Next vision, copy drafts,
SSD read-ahead, first token before the next draft).Read the full README ↗