File size: 5,403 Bytes
61cb4e9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1295954
61cb4e9
 
 
 
 
1295954
61cb4e9
 
 
 
 
 
 
 
 
1295954
 
 
61cb4e9
 
 
1295954
61cb4e9
1295954
61cb4e9
 
 
 
 
 
 
 
 
 
1295954
 
 
61cb4e9
 
 
 
 
1295954
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
61cb4e9
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
---
library_name: mesh-llm
base_model:
- "unsloth/DeepSeek-R1-GGUF"
pipeline_tag: text-generation
tags:
- gguf
- mesh-llm
- layer-package
- skippy
- distributed-inference
- local-inference
- openai-compatible
---

<div align="center">
  <a href="https://www.meshllm.cloud">
    <img src="https://github.com/Mesh-LLM/mesh-llm/raw/main/docs/mesh-llm-logo.svg" alt="Mesh LLM" width="220">
  </a>

  <h1>DeepSeek-R1-Q4_K_M</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 **DeepSeek-R1-Q4_K_M** across a local Mesh LLM cluster.

This package is derived from [unsloth/DeepSeek-R1-GGUF](https://huggingface.co/unsloth/DeepSeek-R1-GGUF) and keeps the original GGUF distribution split into per-layer artifacts for distributed inference.

## Highlights

| Run locally | Pool multiple machines | OpenAI-compatible | Package variant |
|---|---|---|---|
| Private inference on your hardware | Split layers across peers | Serve `/v1/chat/completions` locally | `Q4_K_M` layer package |

## Model Overview

| Property | Value |
|---|---|
| **Source model** | [unsloth/DeepSeek-R1-GGUF](https://huggingface.co/unsloth/DeepSeek-R1-GGUF) |
| **Model id** | `unsloth/DeepSeek-R1-GGUF:DeepSeek-R1-Q4_K_M` |
| **Family** | DeepSeek |
| **Parameter scale** | not recorded |
| **Quantization** | `Q4_K_M` |
| **Layer count** | 61 |
| **Activation width** | 7168 |
| **Package size** | 377.0 GB |
| **Source file** | `DeepSeek-R1-Q4_K_M/DeepSeek-R1-Q4_K_M-00001-of-00009.gguf` |
| **Package repo** | [meshllm/DeepSeek-R1-Q4_K_M-layers](https://huggingface.co/meshllm/DeepSeek-R1-Q4_K_M-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: [unsloth/DeepSeek-R1-GGUF](https://huggingface.co/unsloth/DeepSeek-R1-GGUF).

## Quickstart

```bash
# Run this on each machine that should contribute memory/compute.
mesh-llm serve --model "meshllm/DeepSeek-R1-Q4_K_M-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": "unsloth/DeepSeek-R1-GGUF:DeepSeek-R1-Q4_K_M",
    "messages": [{"role": "user", "content": "Write a tiny hello-world function in Rust."}],
    "max_tokens": 128
  }'
```

## Package Variant

| Property | Value |
|---|---|
| **Format** | `layer-package` |
| **Canonical source ref** | `unsloth/DeepSeek-R1-GGUF@main/DeepSeek-R1-Q4_K_M/DeepSeek-R1-Q4_K_M-00001-of-00009.gguf` |
| **Source revision** | `main` |
| **Source SHA-256** | `d111d9e28b4035e6781906b6451b7866737b4a4ee734baa1575c55d8aa1b4200` |
| **Skippy ABI** | `0.1.22` |
| **Package manifest SHA-256** | `f5a62c4f2f5427ac6e083d7666313832cb61a2fc5d8dacfc317b540d8ac82e9d` |

## What Is Included

| Artifact | Path | Contents | SHA-256 |
|---|---|---|---|
| Manifest | `model-package.json` | Package schema, source identity, checksums | `f5a62c4f2f5427ac6e083d7666313832cb61a2fc5d8dacfc317b540d8ac82e9d` |
| Metadata | `shared/metadata.gguf` | 0 tensors, 5.0 MB | `0e1bf01f20ef69f691126b69c633fd63977cd190bea4182a1c9f41d1537b0ad6` |
| Embeddings | `shared/embeddings.gguf` | 1 tensors, 502.1 MB | `951352774cabdce1e5fe940b30ca85ac8440de68afb6c6eceb451524109991f1` |
| Output head | `shared/output.gguf` | 2 tensors, 730.0 MB | `131fcb580fd1ba667733e39ffc806f819f54928621f40cd47405399a8b9abecb` |
| Transformer layers | `layers/layer-*.gguf` | 61 layer artifacts, 1022 tensors, 375.8 GB | `see 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/DeepSeek-R1-Q4_K_M/DeepSeek-R1-Q4_K_M-00001-of-00009.gguf" --out-dir "/tmp/meshllm-layer-job-meshllm_DeepSeek-R1-Q4_K_M-layers-137/package"
```

## Links

- Source model: [unsloth/DeepSeek-R1-GGUF](https://huggingface.co/unsloth/DeepSeek-R1-GGUF)
- Mesh LLM website: [meshllm.cloud](https://www.meshllm.cloud)
- Mesh LLM: [github.com/Mesh-LLM/mesh-llm](https://github.com/Mesh-LLM/mesh-llm)
- Discord: [discord.gg/rs6fmc63eN](https://discord.gg/rs6fmc63eN)
- Package catalog: [meshllm/catalog](https://huggingface.co/datasets/meshllm/catalog)
- Package format: [layer-package-repos.md](https://github.com/Mesh-LLM/mesh-llm/blob/main/docs/specs/layer-package-repos.md)