Instructions to use second-state/Nemotron-Mini-4B-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries
NeMo
How to use second-state/Nemotron-Mini-4B-Instruct-GGUF with NeMo:
```
# tag did not correspond to a valid NeMo domain.
```

How to use second-state/Nemotron-Mini-4B-Instruct-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="second-state/Nemotron-Mini-4B-Instruct-GGUF",
	filename="NVIDIA-Nemotron-Nano-9B-v2-Q2_K.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 second-state/Nemotron-Mini-4B-Instruct-GGUF 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 second-state/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf second-state/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf second-state/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf second-state/Nemotron-Mini-4B-Instruct-GGUF: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 second-state/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf second-state/Nemotron-Mini-4B-Instruct-GGUF: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 second-state/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf second-state/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M

Use Docker

docker model run hf.co/second-state/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use second-state/Nemotron-Mini-4B-Instruct-GGUF with Ollama:
```
ollama run hf.co/second-state/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M
```

Unsloth Studio

How to use second-state/Nemotron-Mini-4B-Instruct-GGUF 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 second-state/Nemotron-Mini-4B-Instruct-GGUF 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 second-state/Nemotron-Mini-4B-Instruct-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for second-state/Nemotron-Mini-4B-Instruct-GGUF to start chatting

How to use second-state/Nemotron-Mini-4B-Instruct-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf second-state/Nemotron-Mini-4B-Instruct-GGUF: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": "second-state/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use second-state/Nemotron-Mini-4B-Instruct-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf second-state/Nemotron-Mini-4B-Instruct-GGUF: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 second-state/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use second-state/Nemotron-Mini-4B-Instruct-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf second-state/Nemotron-Mini-4B-Instruct-GGUF: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 "second-state/Nemotron-Mini-4B-Instruct-GGUF: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 second-state/Nemotron-Mini-4B-Instruct-GGUF with Docker Model Runner:
```
docker model run hf.co/second-state/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M
```

Lemonade

How to use second-state/Nemotron-Mini-4B-Instruct-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull second-state/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Nemotron-Mini-4B-Instruct-GGUF-Q4_K_M

List all available models

lemonade list

apepkuss79 commited on Sep 16, 2024

Commit

fc85bb7

verified ·

1 Parent(s): 1eacbed

Update README.md

Browse files

Files changed (1) hide show

README.md +20 -11

README.md CHANGED Viewed

@@ -49,23 +49,22 @@ library_name: nemo
     <extra_id_1>Assistant\n
     ```
-    <!-- - Tool use
       ```text
       <extra_id_0>System
-      {system prompt}
-      <tool> ... </tool>
-      <context> ... </context>
       <extra_id_1>User
-      {prompt}
-      <extra_id_1>Assistant
-      <toolcall> ... </toolcall>
       <extra_id_1>Tool
-      {tool response}
       <extra_id_1>Assistant\n
-      ``` -->
 - Context size: `4096`
@@ -79,6 +78,16 @@ library_name: nemo
     --model-name Nemotron-Mini-4B-Instruct
   ```
 - Run as LlamaEdge command app
   ```bash

     <extra_id_1>Assistant\n
     ```
+    - Tool use
       ```text
       <extra_id_0>System
+      {system_message}
+      <tool> {tool_1} </tool>
+      <tool> {tool_2} </tool>
       <extra_id_1>User
+      {user_message_1}<extra_id_1>Assistant
+      <toolcall> {tool_call_message} </toolcall>
       <extra_id_1>Tool
+      {tool_result_message}
       <extra_id_1>Assistant\n
+      ```
 - Context size: `4096`
     --model-name Nemotron-Mini-4B-Instruct
   ```
+  - Tool use
+    ```bash
+    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Nemotron-Mini-4B-Instruct-Q5_K_M.gguf \
+      llama-api-server.wasm \
+      --prompt-template nemotron-tool \
+      --ctx-size 4096 \
+      --model-name Nemotron-Mini-4B-Instruct
+    ```
 - Run as LlamaEdge command app
   ```bash