Instructions to use kishida/llama-3.2-java-error-explainer-jp-cheerful-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use kishida/llama-3.2-java-error-explainer-jp-cheerful-3b with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="kishida/llama-3.2-java-error-explainer-jp-cheerful-3b", filename="java-error-explainer-jp-cheerful-llama-3.2-3b.Q4_K_M.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 kishida/llama-3.2-java-error-explainer-jp-cheerful-3b 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 kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M # Run inference directly in the terminal: llama cli -hf kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M # Run inference directly in the terminal: llama cli -hf kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M
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 kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M
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 kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M
Use Docker
docker model run hf.co/kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use kishida/llama-3.2-java-error-explainer-jp-cheerful-3b with Ollama:
ollama run hf.co/kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M
- Unsloth Studio
How to use kishida/llama-3.2-java-error-explainer-jp-cheerful-3b 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 kishida/llama-3.2-java-error-explainer-jp-cheerful-3b 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 kishida/llama-3.2-java-error-explainer-jp-cheerful-3b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for kishida/llama-3.2-java-error-explainer-jp-cheerful-3b to start chatting
- Pi
How to use kishida/llama-3.2-java-error-explainer-jp-cheerful-3b with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M
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": "kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use kishida/llama-3.2-java-error-explainer-jp-cheerful-3b with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M
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 kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use kishida/llama-3.2-java-error-explainer-jp-cheerful-3b with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M
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 "kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M" \ --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 kishida/llama-3.2-java-error-explainer-jp-cheerful-3b with Docker Model Runner:
docker model run hf.co/kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M
- Lemonade
How to use kishida/llama-3.2-java-error-explainer-jp-cheerful-3b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M
Run and chat with the model
lemonade run user.llama-3.2-java-error-explainer-jp-cheerful-3b-Q4_K_M
List all available models
lemonade list
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": "kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M"
}
]
}
}
}Run Pi
# Start Pi in your project directory:
piJavaのコンパイルエラーを明るく解説します。
from llama_cpp import Llama
# model load
base_model = "llama-3.2-3b"
quant = "Q4_K_M"
llm = Llama.from_pretrained(
repo_id=f"kishida/java-error-explainer-jp-cheerful-{base_model}",
filename=f"java-error-explainer-jp-cheerful-{base_model}.{quant}.gguf",
seed=1234,
)
# streaming
def chat(msg):
res = llm.create_chat_completion(
messages=[
{"role": "system", "content": "You are a Java compile error explainer."},
{"role": "user", "content": msg},
],
temperature=0.7,
)
return res["choices"][0]["message"]["content"]
source = """
void main() {
IO.println(LocalDateTime.now());
IO.println("Hello")
}
"""
error = """
HelloWithError.java:3: エラー: ';'がありません
IO.println("Hello")
^
エラー1個
"""
template = """
source:
{}
compile error:
{}
"""
print("source + error")
print(chat(template.format(source, error)))
"""
あら、コンパイルエラーの原因がわかってるね!3行目のIO.println("Hello")でセミコロンがついていないみたい。Javaでは文の最後に必ずセミコロンが必要なの。IO.println("Hello")っていう文の最後にセミコロンがついていないから、コンパイラが「え?ここで終わっちゃったの?」って混乱しちゃってる。IO.println("Hello")をIO.println("Hello");と書き換えれば解決するわ!
"""
print("error only")
print(chat(error))
"""
IO.println("Hello")って書いちゃってるけど、最後にセミコロンが必要なのよね。Javaは文末にセミコロンを必ず書き込まないとコンパイラーが「え?文の終わりに何があるの?」って混乱してるんだ。セミコロンを追加すれば問題なくなるから、ちゃんとJavaの基本ルールを覚えてみて!
"""
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Base model
meta-llama/Llama-3.2-3B-Instruct
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp# Start a local OpenAI-compatible server: llama serve -hf kishida/llama-3.2-java-error-explainer-jp-cheerful-3b:Q4_K_M