Compress LLM KV cache with TurboQuant
turboquant-pytorchskillsetup L2★0
romeytheAI/Ga-mg ↗What it does
Implement turboquant pytorch workflow
Best for
Implementing turboquant pytorch workflows that require automation.
Outputs
- · Extracted source code or structured data
- · Risk/priority scores
- · Compressed tensors (quantized format)
Requires
- · HTTP client (curl/requests)
- · Python runtime
- · PyTorch
- · Git CLI
Preconditions
None specified
Failure modes
- · Information loss exceeds acceptable threshold
Trust signals
- · Peer-reviewed ICLR 2026 publication