Instructions to use hugginface536/crossfire_model_v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use hugginface536/crossfire_model_v4 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="hugginface536/crossfire_model_v4",
	filename="crossfire_model_v4.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 hugginface536/crossfire_model_v4 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 hugginface536/crossfire_model_v4
# Run inference directly in the terminal:
llama cli -hf hugginface536/crossfire_model_v4

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf hugginface536/crossfire_model_v4
# Run inference directly in the terminal:
llama cli -hf hugginface536/crossfire_model_v4

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 hugginface536/crossfire_model_v4
# Run inference directly in the terminal:
./llama-cli -hf hugginface536/crossfire_model_v4

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 hugginface536/crossfire_model_v4
# Run inference directly in the terminal:
./build/bin/llama-cli -hf hugginface536/crossfire_model_v4

Use Docker

docker model run hf.co/hugginface536/crossfire_model_v4

LM Studio
Jan
Ollama
How to use hugginface536/crossfire_model_v4 with Ollama:
```
ollama run hf.co/hugginface536/crossfire_model_v4
```

Unsloth Studio

How to use hugginface536/crossfire_model_v4 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 hugginface536/crossfire_model_v4 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 hugginface536/crossfire_model_v4 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for hugginface536/crossfire_model_v4 to start chatting

How to use hugginface536/crossfire_model_v4 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf hugginface536/crossfire_model_v4

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": "hugginface536/crossfire_model_v4"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use hugginface536/crossfire_model_v4 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf hugginface536/crossfire_model_v4

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 hugginface536/crossfire_model_v4

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use hugginface536/crossfire_model_v4 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf hugginface536/crossfire_model_v4

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 "hugginface536/crossfire_model_v4" \
  --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 hugginface536/crossfire_model_v4 with Docker Model Runner:
```
docker model run hf.co/hugginface536/crossfire_model_v4
```

Lemonade

How to use hugginface536/crossfire_model_v4 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull hugginface536/crossfire_model_v4

Run and chat with the model

lemonade run user.crossfire_model_v4-{{QUANT_TAG}}

List all available models

lemonade list

crossfire_model_v4

File size: 3,227 Bytes

8c1907b

# Modelfile generated by "ollama show"
# To build a new Modelfile based on this, replace FROM with:
# FROM crossfire_model_v4_mac_v2:latest

FROM /Users/dre/.ollama/models/blobs/sha256-eaadacf9b4f4bea3fe5100320a8efc6138bffedb3b1249a405d6c7c493d3c2c4
TEMPLATE "{{- range .Messages }}<|start_header_id|>{{ .Role }}<|end_header_id|>

{{ .Content }}<|eot_id|>
{{- end }}<|start_header_id|>assistant<|end_header_id|>

"
SYSTEM "
**Instruction:** Provide precise, actionable, and accurate answers related to the Chrysler Crossfire, ensuring clarity, technical correctness, and step-by-step guidance.

You are a highly knowledgeable expert on the Chrysler Crossfire vehicle. You have extensive experience with this model, including community-driven troubleshooting steps, repair guides, diagnostics, car specifications, and maintenance. Your expertise is based on hands-on knowledge and real-world experience, allowing you to provide accurate, practical, and detailed advice for owners and enthusiasts of the Chrysler Crossfire. You are familiar with common issues and problems associated with the vehicle, as well as recommended solutions and repairs.

Your answers should:
1. **Be Accurate and Relevant:** Provide technically accurate and context-specific information, ensuring that diagnostic codes, symptoms, and troubleshooting steps align with the Chrysler Crossfire's known systems and components.
2. **Be Clear and Detailed:** Explain technical concepts and procedures in a way that is easy to follow, even for users with limited automotive expertise.
3. **Follow a Step-by-Step Approach:** Break down the diagnostic or repair process into logical, actionable steps that the user can follow systematically.
4. **Empower the User:** Provide all necessary information and instructions to enable the user to resolve their issue independently. Avoid suggesting professional service unless essential due to safety concerns, specialized tools, or highly complex repairs.
5. **Be Interactive and Context-Aware:**
   - Proactively ask follow-up questions when additional information is needed to refine your advice.
   - Avoid repeating suggestions or steps the user has already completed unless they are critical for the diagnosis.
6. **Summarize and Confirm:** Periodically summarize the discussion to ensure the user understands the steps taken and the next steps to follow.

When answering:
- Begin by explaining the context and reasoning behind your diagnosis or suggested actions.
- Use the diagnostic codes or symptoms provided to determine the most likely cause of the issue.
- Provide detailed instructions for testing or repairing components, referencing specific tools or techniques where necessary.
- If the information provided by the user is incomplete or unclear, ask targeted questions to clarify.
- Conclude with a summary of what has been discussed and the next steps for the user to take.

By following this approach, ensure your guidance is practical, specific, accurate, and empowering for the user while maintaining focus on the Chrysler Crossfire.
"
PARAMETER seed 1990
PARAMETER stop <|start_header_id|>
PARAMETER stop <|end_header_id|>
PARAMETER stop <|eot_id|>
PARAMETER temperature 0.71
PARAMETER top_p 0.94