Instructions to use rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX",
	filename="Jackrong-Qwopus3.6-35B-A3B-Coder-Q3_0_ROCMFPX.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 rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX 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 rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP
# Run inference directly in the terminal:
llama cli -hf rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP
# Run inference directly in the terminal:
llama cli -hf rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP

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 rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP
# Run inference directly in the terminal:
./llama-cli -hf rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP

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 rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP
# Run inference directly in the terminal:
./build/bin/llama-cli -hf rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP

Use Docker

docker model run hf.co/rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP

LM Studio
Jan
Ollama
How to use rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX with Ollama:
```
ollama run hf.co/rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP
```

Unsloth Studio

How to use rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX 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 rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX 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 rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX to start chatting

How to use rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP

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": "rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP

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 rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP

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 "rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP" \
  --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 rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX with Docker Model Runner:
```
docker model run hf.co/rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP
```

Lemonade

How to use rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull rcmorano/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX:Q4_0_ROCMFP

Run and chat with the model

lemonade run user.Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX-Q4_0_ROCMFP

List all available models

lemonade list

my models.ini for llamacpp:

[Jackrong-Qwopus3.6-35B-A3B-Coder-Q8_0_ROCMFPX]
model = /mnt/models/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX/Jackrong-Qwopus3.6-35B-A3B-Coder-Q8_0_ROCMFPX_AGENT.gguf
mmproj = /mnt/models/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX/mmproj-F32.gguf
chat-template-file = /mnt/models/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX/chat_template.jinja
alias = jackrong-qwopus3.6-35b-a3b-coder-q8-rocmfpx
ctx-size = 262144
temp = 0.6
top-p = 0.95
top-k = 20
min-p = 0.0
presence-penalty = 0.0
repeat-penalty = 1.0
device = Vulkan0
spec-type = draft-mtp
spec-draft-device = Vulkan0
spec-draft-n-max = 2
spec-draft-ngl = all
spec-draft-type-k = f16
spec-draft-type-v = f16
spec-draft-n-min=0
spec-draft-p-min=0.0
spec-draft-p-split=0.10
np = 1
chat-template-kwargs = {"preserve_thinking": true}
cache-type-k = q8_0
cache-type-v = q8_0

[Jackrong-Qwopus3.6-35B-A3B-Coder-Q8_0_ROCMFPX-it]
model = /mnt/models/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX/Jackrong-Qwopus3.6-35B-A3B-Coder-Q8_0_ROCMFPX_AGENT.gguf
mmproj = /mnt/models/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX/mmproj-F32.gguf
chat-template-file = /mnt/models/Jackrong-Qwopus3.6-35B-A3B-Coder-ROCMFPX/chat_template.jinja
alias = jackrong-qwopus3.6-35b-a3b-coder-q8-rocmfpx-it
ctx-size = 262144
temp = 0.6
top-p = 0.95
top-k = 20
min-p = 0.0
presence-penalty = 0.0
repeat-penalty = 1.0
reasoning = off
reasoning-format = none
reasoning-budget = -1
no-context-shift = true
device = Vulkan0
spec-type = draft-mtp
spec-draft-device = Vulkan0
spec-draft-n-max = 2
spec-draft-ngl = all
spec-draft-type-k = f16
spec-draft-type-v = f16
spec-draft-n-min=0
spec-draft-p-min=0.0
spec-draft-p-split=0.10
np = 1
cache-type-k = q8_0
cache-type-v = q8_0