Instructions to use bytecode66/froged_N2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use bytecode66/froged_N2.1 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 bytecode66/froged_N2.1:Q8_0
# Run inference directly in the terminal:
llama cli -hf bytecode66/froged_N2.1:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf bytecode66/froged_N2.1:Q8_0
# Run inference directly in the terminal:
llama cli -hf bytecode66/froged_N2.1:Q8_0

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 bytecode66/froged_N2.1:Q8_0
# Run inference directly in the terminal:
./build/bin/llama cli -hf bytecode66/froged_N2.1:Q8_0

Use Docker

docker model run hf.co/bytecode66/froged_N2.1:Q8_0

Llama new
LM Studio
Jan

vLLM

How to use bytecode66/froged_N2.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bytecode66/froged_N2.1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bytecode66/froged_N2.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/bytecode66/froged_N2.1:Q8_0

Ollama
How to use bytecode66/froged_N2.1 with Ollama:
```
ollama run hf.co/bytecode66/froged_N2.1:Q8_0
```
Unsloth Desktop

How to use bytecode66/froged_N2.1 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf bytecode66/froged_N2.1:Q8_0

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": "bytecode66/froged_N2.1:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use bytecode66/froged_N2.1 with Docker Model Runner:
```
docker model run hf.co/bytecode66/froged_N2.1:Q8_0
```

Lemonade

How to use bytecode66/froged_N2.1 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull bytecode66/froged_N2.1:Q8_0

Run and chat with the model

lemonade run user.froged_N2.1-Q8_0

List all available models

lemonade list

Hermes Agent

How to use bytecode66/froged_N2.1 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf bytecode66/froged_N2.1:Q8_0

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 bytecode66/froged_N2.1:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use bytecode66/froged_N2.1 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf bytecode66/froged_N2.1:Q8_0

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 "bytecode66/froged_N2.1:Q8_0" \
  --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"

bytecode66 commited on 8 days ago

Commit

d74fc0e

verified ·

1 Parent(s): 4401cfb

Add model card and safe usage instructions

Browse files

Files changed (1) hide show

README.md +31 -0

README.md ADDED Viewed

	@@ -0,0 +1,31 @@

+---
+tags:
+  - gguf
+  - llama.cpp
+  - text-generation
+  - cybersecurity
+  - devops
+  - coding
+base_model: WhiteRabbitNeo/WhiteRabbitNeo-V3-7B
+pipeline_tag: text-generation
+---
+# Froged_N2.1
+Repositori ini berisi kuantisasi **Q8_0 GGUF** dari WhiteRabbitNeo V3 7B, disalin dari [bartowski/WhiteRabbitNeo_WhiteRabbitNeo-V3-7B-GGUF](https://huggingface.co/bartowski/WhiteRabbitNeo_WhiteRabbitNeo-V3-7B-GGUF). Ukuran berkas sekitar 8,1 GB. Berkas ini ditujukan untuk runtime GGUF seperti `llama.cpp`; model chat berjalan pada perangkat atau server dengan memori yang memadai.
+## Menjalankan dengan llama.cpp
+```bash
+llama-cli -hf bytecode66/froged_N2.1:WhiteRabbitNeo_WhiteRabbitNeo-V3-7B-Q8_0.gguf
+```
+Untuk membuka API lokal yang kompatibel dengan OpenAI:
+```bash
+llama-server -hf bytecode66/froged_N2.1:WhiteRabbitNeo_WhiteRabbitNeo-V3-7B-Q8_0.gguf --host 0.0.0.0 --port 8080
+```
+Gunakan hanya untuk pembelajaran dan pengujian keamanan yang Anda miliki atau telah mendapat izin, termasuk lab dan CTF. Jangan gunakan untuk mengakses atau mengganggu sistem tanpa izin.
+Model sumber dan detail kuantisasi: [bartowski/WhiteRabbitNeo_WhiteRabbitNeo-V3-7B-GGUF](https://huggingface.co/bartowski/WhiteRabbitNeo_WhiteRabbitNeo-V3-7B-GGUF). Model dasar: [WhiteRabbitNeo/WhiteRabbitNeo-V3-7B](https://huggingface.co/WhiteRabbitNeo/WhiteRabbitNeo-V3-7B). Periksa lisensi pada repositori sumber sebelum penggunaan atau redistribusi.