meshllm/Ornith-1.5-35B-Q4_K_M-layers

🤗 Hugging Face 来源text-generationmit激活 35B23 GBGGUF✓ 45 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo meshllm/Ornith-1.5-35B-Q4_K_M-layers ./model-folder
需要做种者 →

Ornith-1.5-35B-Q4_K_M

Distributed GGUF inference package for Mesh LLM

GGUF layer package for running Ornith-1.5-35B-Q4_K_M across a local Mesh LLM cluster.

This package is derived from ornith-ai/Ornith-1.5-35B-A3B-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 ornith-ai/Ornith-1.5-35B-A3B-GGUF
Model id ornith-ai/Ornith-1.5-35B-A3B-GGUF:Q4_K_M
Family Ornith
Parameter scale 35B
Quantization Q4_K_M
Layer count 41
Activation width not recorded
Package size 0 B
Source file Ornith-1.5-35B-Q4_K_M.gguf
Package repo meshllm/Ornith-1.5-35B-Q4_K_M-layers
License mit from ornith-ai/Ornith-1.5-35B-A3B-GGUF

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: ornith-ai/Ornith-1.5-35B-A3B-GGUF.

Quickstart

# Run this on each machine that should contribute memory/compute.
mesh-llm serve --model "meshllm/Ornith-1.5-35B-Q4_K_M-layers" --split
# Check the mesh and discover the OpenAI-compatible model name.
curl -s http://localhost:3131/api/status
curl -s http://localhost:3131/v1/models
# Send an OpenAI-compatible chat request.
curl -s http://localhost:3131/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "ornith-ai/Ornith-1.5-35B-A3B-GGUF:Q4_K_M",
    "messages": [{"role": "user", "content": "Write a tiny hello-world function in Rust."}],
    "max_tokens": 128
  }'

Package Variant

Property Value
Format gguf
Canonical source ref ornith-ai/Ornith-1.5-35B-A3B-GGUF@12393612fd4f730ff5aadc23e9b8f9648aa49ceb/Ornith-1.5-35B-Q4_K_M.gguf
Source revision 12393612fd4f730ff5aadc23e9b8f9648aa49ceb
Source SHA-256 42739874cc2ccfdb8523b23fbe52e29b2a7555c8176737ca9ca0b5d59859d41f
Skippy ABI not recorded
Package manifest SHA-256 397df60b3e66c79633ca741e081e5c53407762df28a3fac4ee3714ddfccd12a9

What Is Included

Artifact Path Contents SHA-256
Manifest model-package.json Package schema, source identity, checksums 397df60b3e66c79633ca741e081e5c53407762df28a3fac4ee3714ddfccd12a9

Validation

Generated by the Mesh LLM HF Jobs splitter from mesh-llm ref 29bdf713d769a45cd299f4a4f7cea5333d700efd. Each artifact is checksummed as it is written, uploaded to this repository, and removed from the job workspace before the next artifact is produced.

skippy-model-package write-package "/hf-cache/Ornith-1.5-35B-Q4_K_M.gguf" --out-dir "/tmp/meshllm-layer-job-meshllm_Ornith-1.5-35B-Q4_K_M-layers-1/package"

Links