Text Generation
Transformers
Safetensors
bailing_hybrid
conversational
custom_code
Eval Results
compressed-tensors
Instructions to use inclusionAI/Ring-2.6-1T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inclusionAI/Ring-2.6-1T with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="inclusionAI/Ring-2.6-1T", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("inclusionAI/Ring-2.6-1T", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use inclusionAI/Ring-2.6-1T with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "inclusionAI/Ring-2.6-1T" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "inclusionAI/Ring-2.6-1T", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/inclusionAI/Ring-2.6-1T
- SGLang
How to use inclusionAI/Ring-2.6-1T 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 "inclusionAI/Ring-2.6-1T" \ --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": "inclusionAI/Ring-2.6-1T", "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 "inclusionAI/Ring-2.6-1T" \ --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": "inclusionAI/Ring-2.6-1T", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use inclusionAI/Ring-2.6-1T with Docker Model Runner:
docker model run hf.co/inclusionAI/Ring-2.6-1T
| {% set reasoning_effort = reasoning_effort | default('high', true) %} | |
| {%- if messages[0].role == 'system' and messages[0].content != '' or tools or (reasoning_effort is defined and reasoning_effort != '') %} | |
| {{- '<role>SYSTEM</role>\n' }} | |
| {%- endif %} | |
| {%- if reasoning_effort is defined and reasoning_effort != '' %} | |
| {{- 'Reasoning: ' + reasoning_effort + '\n\n'}} | |
| {%- endif %} | |
| {%- if messages[0].role == 'system' %} | |
| {%- if messages[0].content != '' %} | |
| {{- messages[0].content }} | |
| {{- '\n\n' if tools else '<|role_end|>\n\n' }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- if tools %} | |
| {{- "# Tools\nYou may call one or more functions to assist with the user query.\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }} | |
| {%- for tool in tools %} | |
| {{- "\n" }} | |
| {{- tool | tojson }} | |
| {%- endfor %} | |
| {{- "\n</tools>\nIf none of the functions can be used, point it out. If the given question lacks the parameters required by the function, also point it out.\nIf you need to use a function, for each function call, output the function name and arguments within the following XML format:\n<tool_call>{function-name}\n<arg_key>{arg-key-1}</arg_key>\n<arg_value>{arg-value-1}</arg_value>\n<arg_key>{arg-key-2}</arg_key>\n<arg_value>{arg-value-2}</arg_value>\n...\n</tool_call><|role_end|>\n\n" }} | |
| {%- endif %} | |
| {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %} | |
| {%- for message in messages[::-1] %} | |
| {%- set index = (messages|length - 1) - loop.index0 %} | |
| {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %} | |
| {%- set ns.multi_step_tool = false %} | |
| {%- set ns.last_query_index = index %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- for message in messages %} | |
| {%- if message.content is string %} | |
| {%- set content = message.content %} | |
| {%- else %} | |
| {%- set content = '' %} | |
| {%- endif %} | |
| {%- if message.role == "user" %} | |
| {{- '<role>HUMAN</role>\n' + message.content + '<|role_end|>\n\n' }} | |
| {%- elif message.role == "system" and not loop.first %} | |
| {{- '<role>SYSTEM</role>\n' + message.content + '<|role_end|>\n\n' }} | |
| {%- elif message.role == "assistant" %} | |
| {%- set reasoning_content = '' %} | |
| {%- if message.reasoning_content is string %} | |
| {%- if message.reasoning_content !='' %} | |
| {%- set reasoning_content = message.reasoning_content %} | |
| {%- endif %} | |
| {%- else %} | |
| {%- if '</think>' in content %} | |
| {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %} | |
| {%- set content = content.split('</think>')[-1].lstrip('\n') %} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- if loop.index0 > ns.last_query_index %} | |
| {%- if reasoning_content != '' %} | |
| {{- '<role>ASSISTANT</role>\n' + '<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }} | |
| {%- else %} | |
| {{- '<role>ASSISTANT</role>\n' + content }} | |
| {%- endif %} | |
| {%- else %} | |
| {{- '<role>ASSISTANT</role>\n' + content }} | |
| {%- endif %} | |
| {%- if message.tool_calls %} | |
| {%- for tool_call in message.tool_calls %} | |
| {%- if (loop.first and content) or (not loop.first) %} | |
| {{- '\n' }} | |
| {%- endif %} | |
| {%- if tool_call.function %} | |
| {%- set tc = tool_call.function %} | |
| {%- endif %} | |
| {{- '<tool_call>' + tc.name }} | |
| {% set _args = tc.arguments %} | |
| {%- for k, v in _args.items() %} | |
| {{- '<arg_key>' + k + '</arg_key>' }} | |
| {{- '\n<arg_value>' }} | |
| {%- if v is string %} | |
| {{- v }} | |
| {%- else %} | |
| {{- v | tojson(ensure_ascii=False) }} | |
| {%- endif %} | |
| {{- '</arg_value>' }} | |
| {%- endfor %} | |
| {{- '\n</tool_call>' }} | |
| {%- endfor %} | |
| {%- endif %} | |
| {{- '<|role_end|>\n\n' }} | |
| {%- elif message.role == "tool" %} | |
| {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %} | |
| {{- '<role>OBSERVATION</role>' }} | |
| {%- endif %} | |
| {{- '\n<tool_response>\n' }} | |
| {{- content }} | |
| {{- '\n</tool_response>' }} | |
| {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %} | |
| {{- '<|role_end|>\n\n' }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- if add_generation_prompt %} | |
| {{- '<role>ASSISTANT</role>' }} | |
| {%- endif %} | |