Instructions to use rcmorano/Qwen3.8-27B-ROCMFPX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use rcmorano/Qwen3.8-27B-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/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX # Run inference directly in the terminal: llama cli -hf rcmorano/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf rcmorano/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX # Run inference directly in the terminal: llama cli -hf rcmorano/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf rcmorano/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX # Run inference directly in the terminal: ./build/bin/llama cli -hf rcmorano/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX
Use Docker
docker model run hf.co/rcmorano/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX
- Llama new
- LM Studio
- Jan
- Ollama
How to use rcmorano/Qwen3.8-27B-ROCMFPX with Ollama:
ollama run hf.co/rcmorano/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX
- Unsloth Desktop
- Pi
How to use rcmorano/Qwen3.8-27B-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/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/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/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use rcmorano/Qwen3.8-27B-ROCMFPX with Docker Model Runner:
docker model run hf.co/rcmorano/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX
- Lemonade
How to use rcmorano/Qwen3.8-27B-ROCMFPX with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull rcmorano/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX
Run and chat with the model
lemonade run user.Qwen3.8-27B-ROCMFPX-Q2_0_ROCMFPX
List all available models
lemonade list
- Hermes Agent
How to use rcmorano/Qwen3.8-27B-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/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX
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/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use rcmorano/Qwen3.8-27B-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/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX
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/Qwen3.8-27B-ROCMFPX:Q2_0_ROCMFPX" \ --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"
File size: 2,285 Bytes
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base_model:
- unsloth/Qwen3.8-27B-GGUF
---
Just plain `llama-quantize`d version of Unsloth's GGUFs :)
My `llama-swap` conf for `Q4_0_ROCMFP4_COHERENT`:
```
"qwen38":
name: "qwen38"
env:
- "MODEL_ID=qwen38"
filters:
stripParams: "temperature, top_k, top_p, repeat_penalty, min_p, presence_penalty"
setParamsByID:
"${MODEL_ID}:low-reasoning":
chat_template_kwargs:
reasoning_effort: low
"${MODEL_ID}:med-reasoning":
chat_template_kwargs:
reasoning_effort: medium
"${MODEL_ID}:instruct-nothink":
temperature: 0.7
top_p: 0.8
min_p: 0.0
presence_penalty: 1.5
repeat_penalty: 1.0
chat_template_kwargs:
enable_thinking: false
preserve_thinking: false
"${MODEL_ID}:reasoning-nothink":
temperature: 0.85
chat_template_kwargs:
enable_thinking: false
preserve_thinking: false
proxy: http://host.docker.internal:${PORT}
cmdStop: docker stop rocmfpx-docker-rocm-llama-${PORT}
cmd: |
${rocmfpx-docker-rocm-llama}
--model /mnt/models/Qwen3.8-27B-ROCMFPX/Qwen3.8-27B-Q4_0_ROCMFP4_COHERENT.gguf
--ctx-size 262144
--ctx-checkpoints 32
--checkpoint-every-n-tokens 8192
--seed 69420
--temperature 1.0
--top-p 0.95
--top-k 20
--min-p 0.0
--presence_penalty 0.0
--repeat_penalty 1.0
--spec-draft-type-k q4_0
--spec-draft-type-v q4_0
--cache-type-k f16
--cache-type-v f16
--spec-type draft-mtp
--spec-draft-ngl all
--spec-draft-n-max 5
--spec-draft-threads 16
--spec-draft-threads-batch 32
--spec-draft-poll 1
--spec-draft-poll-batch 1
--chat-template-kwargs '{"preserve_thinking": true}'
``` |