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tiyuvta
/
Qwen3.8-27B-NVFP4-MTP-GGUF

Text Generation
memra
GGUF
nvfp4
speculative-decoding
mtp
conversational
blackwell
qwen3
Eval Results (legacy)
Model card Files Files and versions
xet
Community
3

Instructions to use tiyuvta/Qwen3.8-27B-NVFP4-MTP-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • memra

    How to use tiyuvta/Qwen3.8-27B-NVFP4-MTP-GGUF with memra:

    # memra serves NVIDIA Blackwell workstation and consumer cards (sm_120a), with a
    # compile-gated Hopper lane. Prebuilt binaries need Linux x86_64 and driver 580+,
    # and no CUDA toolkit.
    curl -fsSL https://raw.githubusercontent.com/avifenesh/memra/main/tools/install.sh | sh
    # One chat-templated generation. In a repo with several GGUF files, append
    # :<substring> to choose one, for example hf:tiyuvta/Qwen3.8-27B-NVFP4-MTP-GGUF:Q4_K_M
    MEMRA_CHAT=1 run-gen hf:tiyuvta/Qwen3.8-27B-NVFP4-MTP-GGUF --prompt "Explain KV caches in one sentence."
    # Or an OpenAI-compatible server on 127.0.0.1:8080.
    MEMRA_MODELS="model=hf:tiyuvta/Qwen3.8-27B-NVFP4-MTP-GGUF" memra-server
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

live api

#2 opened 20 days ago by
Avifenesh

Q5K-mtp Fits 100% VRAM on Dual 5060TI-16gb , and Results from Google Cybersecurity Course 1 tests

2
#1 opened 20 days ago by
AIconjured
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