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lyssquant/GLM-5.2-Q2_K-MTP-Q8-layers

sourceHugging Faceupdated 2mo agoView on Hugging Face
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Model Card

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<h1>GLM-5.2-Q2_K-MTP-Q8</h1>

<p> <strong>Distributed GGUF inference package for Mesh LLM</strong> </p>

<p> <a href="https://www.meshllm.cloud"><img alt="Website" src="https://img.shields.io/badge/Website-meshllm.cloud-111111?style=for-the-badge"></a> <a href="https://github.com/Mesh-LLM/mesh-llm"><img alt="GitHub" src="https://img.shields.io/badge/GitHub-Mesh--LLM-24292f?style=for-the-badge&logo=github"></a> <a href="https://discord.gg/rs6fmc63eN"><img alt="Discord" src="https://img.shields.io/badge/Discord-Join-5865F2?style=for-the-badge&logo=discord&logoColor=white"></a> </p> </div>

GGUF layer package for running GLM-5.2-Q2_K-MTP-Q8 across a local Mesh LLM cluster.

This package is derived from meshllm/GLM-5.2-Q2_K-MTP-Q8-GGUF and keeps the original GGUF distribution split into per-layer artifacts for distributed inference.

Highlights

Run locallyPool multiple machinesOpenAI-compatiblePackage variant
Private inference on your hardwareSplit layers across peersServe /v1/chat/completions locallyQ2_K layer package

Model Overview

PropertyValue
Source modelmeshllm/GLM-5.2-Q2_K-MTP-Q8-GGUF
Model idmeshllm/GLM-5.2-Q2_K-MTP-Q8-GGUF:Q2_K-MTP-Q8
FamilyGLM
Parameter scalenot recorded
QuantizationQ2_K
Layer count79
Activation width6144
Package size260.3 GB
Source fileQ2_K-MTP-Q8/GLM-5.2-Q2_K-MTP-Q8-00001-of-00306.gguf
Package repomeshllm/GLM-5.2-Q2_K-MTP-Q8-layers

Recommended Use

  • Local and private inference with Mesh LLM.
  • Multi-machine serving when the full GGUF is too large for one host.
  • OpenAI-compatible chat/completions workflows through Mesh LLM's local API.

For upstream architecture details, chat template guidance, sampling recommendations, license terms, and benchmark notes, see the source model card: meshllm/GLM-5.2-Q2_K-MTP-Q8-GGUF.

Quickstart

bash
# Run this on each machine that should contribute memory/compute.
mesh-llm serve --model "meshllm/GLM-5.2-Q2_K-MTP-Q8-layers" --split
bash
# Check the mesh and discover the OpenAI-compatible model name.
curl -s http://localhost:3131/api/status
curl -s http://localhost:3131/v1/models
bash
# Send an OpenAI-compatible chat request.
curl -s http://localhost:3131/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "meshllm/GLM-5.2-Q2_K-MTP-Q8-GGUF:Q2_K-MTP-Q8",
    "messages": [{"role": "user", "content": "Write a tiny hello-world function in Rust."}],
    "max_tokens": 128
  }'

Package Variant

PropertyValue
Formatlayer-package
Canonical source refmeshllm/GLM-5.2-Q2_K-MTP-Q8-GGUF@main/Q2_K-MTP-Q8/GLM-5.2-Q2_K-MTP-Q8-00001-of-00306.gguf
Source revisionmain
Source SHA-2566e1841a844cae68f434d7f699e1e974232a687e700ad7b26631d6880eb541b9a
Skippy ABI0.1.27
Package manifest SHA-2560df2893e5d1e553b9901c944d0ceae959ee69a949d8a2e69c645f8cae3d91257

What Is Included

ArtifactPathContentsSHA-256
Manifestmodel-package.jsonPackage schema, source identity, checksums0df2893e5d1e553b9901c944d0ceae959ee69a949d8a2e69c645f8cae3d91257
Metadatashared/metadata.gguf0 tensors, 9.0 MBd239e9f5bb3151e29fa2f1f55c53eff16af5737e06afe541c6f24016d74bc8d6
Embeddingsshared/embeddings.gguf1 tensors, 973.2 MBf5694c010726da17a33d68e0bf91566b91f9ccc9bfc08da393faf4c6cfa545b2
Output headshared/output.gguf2 tensors, 1.8 GBb2e3fb2597217dd42464a10c02ec9a866571b37ea61c59d59a9ac84e29db6e50
Transformer layerslayers/layer-*.gguf79 layer artifacts, 1521 tensors, 257.6 GBsee model-package.json

Validation

Generated by the Mesh LLM HF Jobs splitter from mesh-llm ref main. Each artifact is checksummed as it is written, uploaded to this repository, and removed from the job workspace before the next artifact is produced.

bash
skippy-model-package write-package "/source/Q2_K-MTP-Q8/GLM-5.2-Q2_K-MTP-Q8-00001-of-00306.gguf" --out-dir "/tmp/meshllm-layer-job-meshllm_GLM-5.2-Q2_K-MTP-Q8-layers-193/package"

Links