Instructions to use nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM 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 nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16 # Run inference directly in the terminal: llama cli -hf nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16 # Run inference directly in the terminal: llama cli -hf nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
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 nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16 # Run inference directly in the terminal: ./llama-cli -hf nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
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 nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
Use Docker
docker model run hf.co/nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
- LM Studio
- Jan
- vLLM
How to use nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
- SGLang
How to use nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM with Ollama:
ollama run hf.co/nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
- Unsloth Desktop
- Pi
How to use nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
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": "nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM with Docker Model Runner:
docker model run hf.co/nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
- Lemonade
How to use nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
Run and chat with the model
lemonade run user.Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM-BF16
List all available models
lemonade list
- Hermes Agent
How to use nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
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 nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16
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 "nuottroisaoduoc/Elbaz-NVIDIA-Nemotron-3-Nano-30B-A3B-PRISM:BF16" \ --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"
| {{- bos_token -}} | |
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| {%- if json_dict is mapping %} | |
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| {%- endfor %} | |
| {%- endif %} | |
| {% endmacro %} | |
| {%- set enable_thinking = enable_thinking if enable_thinking is defined else True %} | |
| {%- set truncate_history_thinking = truncate_history_thinking if truncate_history_thinking is defined else True %} | |
| {%- set ns = namespace(last_user_idx = -1) %} | |
| {%- set loop_messages = messages %} | |
| {%- for m in loop_messages %} | |
| {%- if m["role"] == "user" %} | |
| {%- set ns.last_user_idx = loop.index0 %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- if messages[0]["role"] == "system" %} | |
| {%- set system_message = messages[0]["content"] %} | |
| {%- set loop_messages = messages[1:] %} | |
| {%- else %} | |
| {%- set system_message = "" %} | |
| {%- set loop_messages = messages %} | |
| {%- endif %} | |
| {%- if not tools is defined %} | |
| {%- set tools = [] %} | |
| {%- endif %} | |
| {# Recompute last_user_idx relative to loop_messages after handling system #} | |
| {%- set ns = namespace(last_user_idx = -1) %} | |
| {%- for m in loop_messages %} | |
| {%- if m["role"] == "user" %} | |
| {%- set ns.last_user_idx = loop.index0 %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- if system_message is defined %} | |
| {{- "<|im_start|>system\n" + system_message }} | |
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| {%- endif %} | |
| {%- endif %} | |
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| {%- if system_message is defined and system_message | length > 0 %} | |
| {{- "\n\n" }} | |
| {%- endif %} | |
| {{- "# Tools\n\nYou have access to the following functions:\n\n" }} | |
| {{- "<tools>" }} | |
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| {%- endif %} | |
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| {%- endif %} | |
| {{- '\n<parameters>' }} | |
| {%- if tool.parameters is defined and tool.parameters is mapping and tool.parameters.properties is defined and tool.parameters.properties is mapping %} | |
| {%- for param_name, param_fields in tool.parameters.properties|items %} | |
| {{- '\n<parameter>' }} | |
| {{- '\n<n>' ~ param_name ~ '</n>' }} | |
| {%- if param_fields.type is defined %} | |
| {{- '\n<type>' ~ (param_fields.type | string) ~ '</type>' }} | |
| {%- endif %} | |
| {%- if param_fields.description is defined %} | |
| {{- '\n<description>' ~ (param_fields.description | trim) ~ '</description>' }} | |
| {%- endif %} | |
| {%- if param_fields.enum is defined %} | |
| {{- '\n<enum>' ~ (param_fields.enum | tojson) ~ '</enum>' }} | |
| {%- endif %} | |
| {%- set handled_keys = ['name', 'type', 'description', 'enum'] %} | |
| {{- render_extra_keys(param_fields, handled_keys) }} | |
| {{- '\n</parameter>' }} | |
| {%- endfor %} | |
| {%- endif %} | |
| {% set handled_keys = ['type', 'properties', 'required'] %} | |
| {{- render_extra_keys(tool.parameters, handled_keys) }} | |
| {%- if tool.parameters is defined and tool.parameters.required is defined %} | |
| {{- '\n<required>' ~ (tool.parameters.required | tojson) ~ '</required>' }} | |
| {%- endif %} | |
| {{- '\n</parameters>' }} | |
| {%- set handled_keys = ['type', 'name', 'description', 'parameters'] %} | |
| {{- render_extra_keys(tool, handled_keys) }} | |
| {{- '\n</function>' }} | |
| {%- endfor %} | |
| {{- "\n</tools>" }} | |
| {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }} | |
| {%- endif %} | |
| {%- if system_message is defined %} | |
| {{- '<|im_end|>\n' }} | |
| {%- else %} | |
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| {{- '<|im_end|>\n' }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- for message in loop_messages %} | |
| {%- if message.role == "assistant" %} | |
| {# Add reasoning content in to content field for unified processing below. #} | |
| {%- if message.reasoning_content is defined and message.reasoning_content is string and message.reasoning_content | trim | length > 0 %} | |
| {%- set content = "<think>\n" ~ message.reasoning_content ~ "\n</think>\n" ~ (message.content | default('', true)) %} | |
| {%- else %} | |
| {%- set content = message.content | default('', true) %} | |
| {%- if content is string -%} | |
| {# Allow downstream logic to to take care of broken thought, only handle coherent reasoning here. #} | |
| {%- if '<think>' not in content and '</think>' not in content -%} | |
| {%- set content = "<think></think>" ~ content -%} | |
| {%- endif -%} | |
| {%- else -%} | |
| {%- set content = content -%} | |
| {%- endif -%} | |
| {%- endif %} | |
| {%- if message.tool_calls is defined and message.tool_calls is iterable and message.tool_calls | length > 0 %} | |
| {# Assistant message has tool calls. #} | |
| {{- '<|im_start|>assistant\n' }} | |
| {%- set include_content = not (truncate_history_thinking and loop.index0 < ns.last_user_idx) %} | |
| {%- if content is string and content | trim | length > 0 %} | |
| {%- if include_content %} | |
| {{- (content | trim) ~ '\n' -}} | |
| {%- else %} | |
| {%- set c = (content | string) %} | |
| {%- if '</think>' in c %} | |
| {# Keep only content after the last closing think. Also generation prompt causes this. #} | |
| {%- set c = c.split('</think>')[-1] %} | |
| {%- elif '<think>' in c %} | |
| {# If <think> was opened but never closed, drop the trailing think segment #} | |
| {%- set c = c.split('<think>')[0] %} | |
| {%- endif %} | |
| {%- set c = "<think></think>" ~ c | trim %} | |
| {%- if c | length > 0 %} | |
| {{- c ~ '\n' -}} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- else %} | |
| {{- "<think></think>" -}} | |
| {%- endif %} | |
| {%- for tool_call in message.tool_calls %} | |
| {%- if tool_call.function is defined %} | |
| {%- set tool_call = tool_call.function %} | |
| {%- endif %} | |
| {{- '<tool_call>\n<function=' ~ tool_call.name ~ '>\n' -}} | |
| {%- if tool_call.arguments is defined %} | |
| {%- if tool_call.arguments is string %} | |
| {%- set args = tool_call.arguments | tojson | fromjson %} | |
| {%- else %} | |
| {%- set args = tool_call.arguments %} | |
| {%- endif %} | |
| {%- for args_name, args_value in args|items %} | |
| {{- '<parameter=' ~ args_name ~ '>\n' -}} | |
| {%- set args_value = args_value | tojson if args_value is mapping or (args_value is iterable and args_value is not string) else args_value | string %} | |
| {{- args_value ~ '\n</parameter>\n' -}} | |
| {%- endfor %} | |
| {%- endif %} | |
| {{- '</function>\n</tool_call>\n' -}} | |
| {%- endfor %} | |
| {{- '<|im_end|>\n' }} | |
| {%- else %} | |
| {# Assistant message doesn't have tool calls. #} | |
| {%- if not (truncate_history_thinking and loop.index0 < ns.last_user_idx) %} | |
| {{- '<|im_start|>assistant\n' ~ (content | default('', true) | string | trim) ~ '<|im_end|>\n' }} | |
| {%- else %} | |
| {%- set c = (content | default('', true) | string) %} | |
| {%- if '<think>' in c and '</think>' in c %} | |
| {%- set c = "<think></think>" ~ c.split('</think>')[-1] %} | |
| {%- endif %} | |
| {%- set c = c | trim %} | |
| {%- if c | length > 0 %} | |
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| {%- else %} | |
| {{- '<|im_start|>assistant\n<|im_end|>\n' }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- elif message.role == "user" or message.role == "system" %} | |
| {{- '<|im_start|>' + message.role + '\n' }} | |
| {%- set content = message.content | string %} | |
| {{- content }} | |
| {{- '<|im_end|>\n' }} | |
| {%- elif message.role == "tool" %} | |
| {%- if loop.previtem and loop.previtem.role != "tool" %} | |
| {{- '<|im_start|>user\n' }} | |
| {%- endif %} | |
| {{- '<tool_response>\n' }} | |
| {{- message.content }} | |
| {{- '\n</tool_response>\n' }} | |
| {%- if not loop.last and loop.nextitem.role != "tool" %} | |
| {{- '<|im_end|>\n' }} | |
| {%- elif loop.last %} | |
| {{- '<|im_end|>\n' }} | |
| {%- endif %} | |
| {%- else %} | |
| {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>\n' }} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- if add_generation_prompt %} | |
| {%- if enable_thinking %} | |
| {{- '<|im_start|>assistant\n<think>\n' }} | |
| {%- else %} | |
| {{- '<|im_start|>assistant\n<think></think>' }} | |
| {%- endif %} | |
| {%- endif %} |