Text Generation
Transformers
Safetensors
exaone_moe
lg-ai
exaone
k-exaone
Mixture of Experts
conversational
Instructions to use LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark") model = AutoModelForCausalLM.from_pretrained("LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark
- SGLang
How to use LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark 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 "LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark" \ --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": "LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark", "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 "LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark" \ --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": "LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark with Docker Model Runner:
docker model run hf.co/LGAI-EXAONE/K-EXAONE-2.0-750B-A37B-DSpark
File size: 6,647 Bytes
5e72b87 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 | {% set image_count = namespace(value=0) %}
{% set video_count = namespace(value=0) %}
{%- set role_indicators = {
'user': '<|user|>\n',
'assistant': '<|assistant|>\n',
'system': '<|system|>\n',
'tool': '<|tool|>\n',
'tool_declare': '<|tool_declare|>\n'
} %}
{%- set end_of_turn = '<|endofturn|>\n' %}
{%- macro declare_available_tools(tools) %}
{{- "# Tools\n" }}
{{- "The available tools are defined below in JSON format.\n" }}
{{- "When calling a tool, use XML with <function=...> and one <parameter=...> block per argument.\n" }}
{{- "\n" }}
{%- for tool in tools %}
{{- "<tool>" }}
{{- tool | tojson(ensure_ascii=False) | safe }}
{{- "</tool>\n" }}
{%- endfor %}
{{- "\n# Tool Call Format\n" }}
{{- "<tool_call>\n" }}
{{- "<function=example_tool_name>\n" }}
{{- "<parameter=arg1>\n" }}
{{- "value1\n" }}
{{- "</parameter>\n" }}
{{- "<parameter=arg2>\n" }}
{{- "2\n" }}
{{- "</parameter>\n" }}
{{- "</function>\n" }}
{{- "</tool_call>" }}
{%- endmacro %}
{%- macro render_tool_call(tool_call, arguments) %}
{{- "<tool_call>\n" }}
{{- "<function=" }}{{- tool_call.name }}{{- ">\n" }}
{%- for args_name, args_value in arguments.items() %}
{{- "<parameter=" }}{{- args_name }}{{- ">\n" }}
{%- if args_value is string %}
{{- args_value }}
{%- else %}
{{- args_value | tojson(ensure_ascii=False) | safe }}
{%- endif %}
{{- "\n</parameter>\n" }}
{%- endfor %}
{{- "</function>\n" }}
{{- "</tool_call>" }}
{%- endmacro %}
{%- macro render_tool_response(msg) %}
{{- "<tool_result>" }}
{%- if msg.content is defined %}
{%- if msg.content is string %}
{{- msg.content }}
{%- else %}
{{- msg.content | tojson(ensure_ascii=False) | safe }}
{%- endif %}
{%- endif %}
{{- "</tool_result>" }}
{%- endmacro %}
{%- set ns = namespace(last_query_index = messages|length - 1, last_query_index_not_yet_determined = true) %}
{%- for message in messages[::-1] %}
{%- set index = (messages|length - 1) - loop.index0 %}
{%- if ns.last_query_index_not_yet_determined and message.role == "user" and message.content is string %}
{%- set ns.last_query_index = index -%}
{%- set ns.last_query_index_not_yet_determined = false -%}
{%- endif %}
{%- endfor %}
{%- if tools is defined and tools %}
{{- role_indicators['tool_declare'] }}
{{- declare_available_tools(tools) }}
{{- end_of_turn -}}
{%- endif %}
{%- for i in range(messages | length) %}
{%- set msg = messages[i] %}
{%- set role = msg.role %}
{%- if role not in role_indicators %}
{{- raise_exception('Unknown role: ' ~ role) }}
{%- endif %}
{%- if i == 0 %}
{%- if role == 'system' %}
{{- role_indicators['system'] }}
{{- msg.content }}
{{- end_of_turn -}}
{%- continue %}
{%- endif %}
{%- endif %}
{%- if role == 'assistant' %}
{{- role_indicators['assistant'] }}
{%- set content = (msg.content if (msg.content is defined and msg.content) else "") -%}
{%- set reasoning = none -%}
{%- if msg.reasoning_content is defined and msg.reasoning_content %}
{%- set reasoning = msg.reasoning_content.strip() -%}
{%- elif content and "</think>" in content %}
{%- set _parts = content.split('</think>') -%}
{%- set reasoning = _parts[0].lstrip('<think>').strip() -%}
{%- set content = _parts[-1].strip() -%}
{%- endif %}
{%- if not (reasoning and ((preserve_thinking is defined and preserve_thinking) or i > ns.last_query_index))%}
{%- set reasoning = none %}
{%- endif %}
{%- if content is string %}
{%- set content = content.strip() -%}
{%- endif %}
{{- "<think>\n" }}
{{- (reasoning if reasoning is not none else "") }}
{{- "\n</think>\n\n" }}
{{- content }}
{%- if msg.tool_calls %}
{%- if content is defined and content %}
{{- "\n" }}
{%- endif %}
{%- for tool_call in msg.tool_calls %}
{%- if tool_call.function is defined %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{%- if tool_call.arguments is defined %}
{%- set arguments = tool_call.arguments %}
{%- elif tool_call.parameters is defined %}
{%- set arguments = tool_call.parameters %}
{%- else %}
{{- raise_exception('arguments or parameters are mandatory: ' ~ tool_call) }}
{%- endif %}
{{- render_tool_call(tool_call, arguments) }}
{%- if not loop.last %}
{{- "\n" }}
{%- endif %}
{%- endfor %}
{%- endif %}
{{- end_of_turn -}}
{%- elif role == "tool" %}
{%- if i == 0 or messages[i - 1].role != "tool" %}
{{- role_indicators['tool'] }}
{%- endif %}
{{- render_tool_response(msg) }}
{%- if loop.last or messages[i + 1].role != "tool" %}
{{- end_of_turn -}}
{%- else %}
{{- "\n" }}
{%- endif %}
{%- else %}
{{- role_indicators[role] }}
{%- if msg.content is string %}
{{- msg.content }}
{%- else %}
{%- for content in msg.content %}
{%- if content.type == 'image' %}
{%- set image_count.value = image_count.value + 1 %}
{%- if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<vision><image_pad></vision>
{%- elif content.type == 'video' %}
{%- set video_count.value = video_count.value + 1 %}
{%- if add_vision_id %}Video {{ video_count.value }}: {% endif %}<vision><video_pad></vision>
{%- elif content.type == 'text' %}
{{- content.text }}
{%- else %}
{{- content.text }}
{%- endif %}
{%- endfor %}
{%- endif %}
{{- end_of_turn -}}
{%- endif %}
{% endfor %}
{%- if add_generation_prompt %}
{{- role_indicators['assistant'] }}
{%- if enable_thinking is not defined or enable_thinking is true %}
{{- "<think>\n" }}
{%- else %}
{{- "<think>\n\n</think>\n\n" }}
{%- endif %}
{%- endif %}
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