Instructions to use JGZYES/ParlzStar-X with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use JGZYES/ParlzStar-X with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen3-4B-Instruct-2507-bnb-4bit") model = PeftModel.from_pretrained(base_model, "JGZYES/ParlzStar-X") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use JGZYES/ParlzStar-X 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 JGZYES/ParlzStar-X # Run inference directly in the terminal: llama cli -hf JGZYES/ParlzStar-X
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf JGZYES/ParlzStar-X # Run inference directly in the terminal: llama cli -hf JGZYES/ParlzStar-X
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 JGZYES/ParlzStar-X # Run inference directly in the terminal: ./llama-cli -hf JGZYES/ParlzStar-X
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 JGZYES/ParlzStar-X # Run inference directly in the terminal: ./build/bin/llama-cli -hf JGZYES/ParlzStar-X
Use Docker
docker model run hf.co/JGZYES/ParlzStar-X
- LM Studio
- Jan
- Ollama
How to use JGZYES/ParlzStar-X with Ollama:
ollama run hf.co/JGZYES/ParlzStar-X
- Unsloth Desktop
- Pi
How to use JGZYES/ParlzStar-X with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf JGZYES/ParlzStar-X
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": "JGZYES/ParlzStar-X" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use JGZYES/ParlzStar-X with Docker Model Runner:
docker model run hf.co/JGZYES/ParlzStar-X
- Lemonade
How to use JGZYES/ParlzStar-X with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull JGZYES/ParlzStar-X
Run and chat with the model
lemonade run user.ParlzStar-X-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use JGZYES/ParlzStar-X with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf JGZYES/ParlzStar-X
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 JGZYES/ParlzStar-X
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use JGZYES/ParlzStar-X with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf JGZYES/ParlzStar-X
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 "JGZYES/ParlzStar-X" \ --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"
ParlzStar X
ParlzStar X ๆฏไธไธชๅบไบ Qwen3-4B ๅพฎ่ฐ็ไปฃ็ ๅฉๆ๏ผ็ฑ JGZ_YES ่ฎญ็ปใ
ๆจกๅไฟกๆฏ
| ้กน็ฎ | ๅ ๅฎน |
|---|---|
| ๅบๅบงๆจกๅ | Qwen/Qwen3-4B |
| ่ฎญ็ปๆนๆณ | QLoRA (r=16, alpha=16) |
| ่ฎญ็ปๆฐๆฎ | Chinese-Instruct-Lite code ๅญ้ (3000ๆก) + ๅๆ่บซไปฝๆฐๆฎ (1000ๆก) |
| ่ฎญ็ปๆญฅๆฐ | 800 ๆญฅ |
| ๆ็ป loss | 0.4154 |
| ่ฎญ็ป็กฌไปถ | RTX 5060 8GB |
| ่ฎญ็ป่ | JGZ_YES |
่ฝๅ
- ไปฃ็ ็ๆ๏ผPythonใC++ใJavaใRustใJavaScript ็ญ
- ็ฎๆณๅฎ็ฐ๏ผๆๅบใๆฅๆพใๅจๆ่งๅใๆฐๆฎ็ปๆ
- ไปฃ็ ่งฃ้ไธ่ฐ่ฏ
- ่บซไปฝ่ฎค็ฅ๏ผ็ฅ้่ชๅทฑๆฏ ParlzStar X๏ผ็ฑ JGZ_YES ่ฎญ็ป
ไฝฟ็จๆนๅผ
ๅ ่ฝฝ LoRA ้้ ๅจ๏ผ
from unsloth import FastLanguageModel
model, tokenizer = FastLanguageModel.from_pretrained(
model_name="JGZYES/ParlzStar-X",
max_seq_length=2048,
load_in_4bit=True,
)
FastLanguageModel.for_inference(model)
ไฝฟ็จ GGUF๏ผ
llama-cli -m parlzstar-x-q4km.gguf -c 4096 -ngl 99 --repeat-penalty 1.3
ๆไปถ่ฏดๆ
| ๆไปถ | ่ฏดๆ |
|---|---|
| adapter_model.safetensors | LoRA ๆ้ |
| adapter_config.json | LoRA ้ ็ฝฎ |
| parlzstar-x-q4km.gguf | Q4_K_M ้ๅ๏ผ็บฆ 2.4GB |
| parlzstar-x-q6k.gguf | Q6_K ้ๅ๏ผ็บฆ 3.1GB |
| parlzstar-x-q8.gguf | Q8_0 ้ๅ๏ผ็บฆ 4.0GB |
ๅฑ้ๆง
4B ๅๆฐ่งๆจก๏ผๅคๆ็ฎๆณๆจ็่ฝๅๆ้
็ๆ็ไปฃ็ ่ฏทๅกๅฟ ้ช่ฏๅๅไฝฟ็จ
ๅถๅฐไผ่พๅบ็นๆฎๆ ็ญพ๏ผๆจ็ๆถๅฏ็จ stop_strings ่ฟๆปค
่บซไปฝ่ฎค็ฅๅถๅฐๅญๅจๆณขๅจ
่ฎธๅฏ่ฏ
ๆฌๆจกๅๅบไบ Qwen/Qwen3-4B ่ฎญ็ปใ่ฎญ็ปๆฐๆฎ Chinese-Instruct-Lite ไฝฟ็จ CC BY-NC-SA 4.0 ่ฎธๅฏ่ฏ๏ผๅ ๆญคๆฌๆจกๅๅๆ ท้็จ CC BY-NC-SA 4.0๏ผ็ฆๆญขๅไธ็จ้ใ
ๅผ็จ
@misc{parlzstar-x,
title={ParlzStar X},
author={JGZ_YES},
year={2025},
url={https://huggingface.co/JGZYES/ParlzStar-X}
}
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