Instructions to use bartowski/Nemotron-Mini-4B-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use bartowski/Nemotron-Mini-4B-Instruct-GGUF with NeMo:
# tag did not correspond to a valid NeMo domain.
- llama-cpp-python
How to use bartowski/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="bartowski/Nemotron-Mini-4B-Instruct-GGUF", filename="Nemotron-Mini-4B-Instruct-IQ3_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use bartowski/Nemotron-Mini-4B-Instruct-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf bartowski/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/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-server -hf bartowski/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/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 bartowski/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bartowski/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 bartowski/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bartowski/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M
Use Docker
docker model run hf.co/bartowski/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use bartowski/Nemotron-Mini-4B-Instruct-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bartowski/Nemotron-Mini-4B-Instruct-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bartowski/Nemotron-Mini-4B-Instruct-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/bartowski/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M
- Ollama
How to use bartowski/Nemotron-Mini-4B-Instruct-GGUF with Ollama:
ollama run hf.co/bartowski/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M
- Unsloth Studio
How to use bartowski/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 bartowski/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 bartowski/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 bartowski/Nemotron-Mini-4B-Instruct-GGUF to start chatting
- Pi
How to use bartowski/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-server -hf bartowski/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": "bartowski/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use bartowski/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-server -hf bartowski/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 bartowski/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use bartowski/Nemotron-Mini-4B-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/Nemotron-Mini-4B-Instruct-GGUF:Q4_K_M
- Lemonade
How to use bartowski/Nemotron-Mini-4B-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/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
Upload 5 files
#2
by Jiqing - opened
- .gitattributes +1 -0
- chat_template.jinja +15 -0
- special_tokens_map.json +1 -0
- tokenizer.json +3 -0
- tokenizer.model +3 -0
- tokenizer_config.json +12 -0
.gitattributes
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@@ -52,3 +52,4 @@ Nemotron-Mini-4B-Instruct-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
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Nemotron-Mini-4B-Instruct-IQ3_M.gguf filter=lfs diff=lfs merge=lfs -text
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Nemotron-Mini-4B-Instruct-f16.gguf filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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{{'<extra_id_0>System'}}{% for message in messages %}{% if message['role'] == 'system' %}{{'
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' + message['content'].strip()}}{% if tools or contexts %}{{'
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'}}{% endif %}{% endif %}{% endfor %}{% if tools %}{% for tool in tools %}{{ '
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<tool> ' + tool|tojson + ' </tool>' }}{% endfor %}{% endif %}{% if contexts %}{% if tools %}{{'
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<context> ' + context.strip() + ' </context>' }}{% endfor %}{% endif %}{{'
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'}}{% for message in messages %}{% if message['role'] == 'user' %}{{ '<extra_id_1>User
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' }}{% elif message['role'] == 'assistant' %}{{ '<extra_id_1>Assistant
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' + message['content'].strip() + '
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' }}{% elif message['role'] == 'tool' %}{{ '<extra_id_1>Tool
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' }}{% endif %}{% endfor %}{{'<extra_id_1>Assistant
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version https://git-lfs.github.com/spec/v1
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oid sha256:f1f39bcb3ba1b42457ec34b6cde2cb7ccffa82a077997c9aed8c5ee687779451
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"added_tokens_decoder": {},
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"model_type": "llama",
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"pad_token_id": null,
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"tokenizer_class": "PreTrainedTokenizerFast",
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"unk_token_id": null
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