Instructions to use JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf",
	filename="Q8_0.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0
# Run inference directly in the terminal:
llama cli -hf JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0
# Run inference directly in the terminal:
llama cli -hf JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0

Use Docker

docker model run hf.co/JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0

LM Studio
Jan
Ollama
How to use JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf with Ollama:
```
ollama run hf.co/JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0
```

Unsloth Studio

How to use JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf to start chatting

How to use JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf with Docker Model Runner:
```
docker model run hf.co/JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0
```

Lemonade

How to use JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull JagjeevanAK/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf:Q8_0

Run and chat with the model

lemonade run user.Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf-Q8_0

List all available models

lemonade list

Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-gguf

About

This repository hosts GGUF files mirrored from:

Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-GGUF

I am not claiming the original training work for the weights currently uploaded here. This repo is intended as a re-upload / mirror of the upstream GGUF release under my Hugging Face account.

If you want the original training details, methodology, and upstream credits, please read the source model card linked above.

Provenance

Original base family: Qwen/Qwen3.5-27B
Upstream distilled GGUF release: Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-GGUF
Format in this repo: GGUF

Intended Use

This repo is for local inference with GGUF-compatible runtimes such as:

llama.cpp
LM Studio
KoboldCpp
other GGUF-compatible tooling

Important Note

The files currently uploaded in this repository should be understood as mirrored artifacts from the upstream release.

Any datasets mentioned below under future work are not claimed as the training data for the weights currently hosted in this repo.

Future Work

For future personal distillation experiments, I plan to work with datasets such as:

These are listed here for transparency about planned work only. They were not used to produce the current mirrored GGUF files in this repository.

Credits

Credit for the original model and training work belongs to the upstream creators and contributors, especially:

Jackrong
Qwen
the dataset authors referenced by the upstream model card

License

Please follow the license and usage terms of the upstream model and all upstream components.

At the time this README was written, the upstream GGUF repository listed the license as apache-2.0. If the upstream licensing or attribution requirements change, this mirror should be updated accordingly.