Instructions to use RedHatAI/GLM-5.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RedHatAI/GLM-5.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="RedHatAI/GLM-5.1") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("RedHatAI/GLM-5.1") model = AutoModelForCausalLM.from_pretrained("RedHatAI/GLM-5.1") 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
- vLLM
How to use RedHatAI/GLM-5.1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "RedHatAI/GLM-5.1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RedHatAI/GLM-5.1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/RedHatAI/GLM-5.1
- SGLang
How to use RedHatAI/GLM-5.1 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 "RedHatAI/GLM-5.1" \ --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": "RedHatAI/GLM-5.1", "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 "RedHatAI/GLM-5.1" \ --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": "RedHatAI/GLM-5.1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use RedHatAI/GLM-5.1 with Docker Model Runner:
docker model run hf.co/RedHatAI/GLM-5.1
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a8e008e | 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 | [gMASK]<sop>
{%- if tools -%}
{%- macro tool_to_json(tool) -%}
{%- set ns_tool = namespace(first=true) -%}
{{ '{' -}}
{%- for k, v in tool.items() -%}
{%- if k != 'defer_loading' and k != 'strict' -%}
{%- if not ns_tool.first -%}{{- ', ' -}}{%- endif -%}
{%- set ns_tool.first = false -%}
"{{ k }}": {{ v | tojson(ensure_ascii=False) }}
{%- endif -%}
{%- endfor -%}
{{- '}' -}}
{%- endmacro -%}
<|system|>
# Tools
You may call one or more functions to assist with the user query.
You are provided with function signatures within <tools></tools> XML tags:
<tools>
{% for tool in tools %}
{%- if 'function' in tool -%}
{%- set tool = tool['function'] -%}
{%- endif -%}
{% if tool.defer_loading is not defined or not tool.defer_loading %}
{{ tool_to_json(tool) }}
{% endif %}
{% endfor %}
</tools>
For each function call, output the function name and arguments within the following XML format:
<tool_call>{function-name}<arg_key>{arg-key-1}</arg_key><arg_value>{arg-value-1}</arg_value><arg_key>{arg-key-2}</arg_key><arg_value>{arg-value-2}</arg_value>...</tool_call>{%- endif -%}
{%- macro visible_text(content) -%}
{%- if content is string -%}
{{- content }}
{%- elif content is iterable and content is not mapping -%}
{%- for item in content -%}
{%- if item is mapping and item.type == 'text' -%}
{{- item.text }}
{%- elif item is string -%}
{{- item }}
{%- endif -%}
{%- endfor -%}
{%- else -%}
{{- content }}
{%- endif -%}
{%- endmacro -%}
{%- set ns = namespace(last_user_index=-1, thinking_indices='') -%}
{%- for m in messages %}
{%- if m.role == 'user' %}
{%- set ns.last_user_index = loop.index0 -%}
{%- elif m.role == 'assistant' %}
{%- if m.reasoning_content is string %}
{%- set ns.thinking_indices = ns.thinking_indices ~ ',' ~ ns.last_user_index ~ ',' -%}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- set ns.has_thinking = false -%}
{%- for m in messages -%}
{%- if m.role == 'user' -%}<|user|>{{ visible_text(m.content) }}{% set ns.has_thinking = (',' ~ loop.index0 ~ ',') in ns.thinking_indices -%}
{%- elif m.role == 'assistant' -%}
<|assistant|>
{%- set content = visible_text(m.content) %}
{%- if m.reasoning_content is string %}
{%- set reasoning_content = m.reasoning_content %}
{%- elif '</think>' in content %}
{%- set reasoning_content = content.split('</think>')[0].split('<think>')[-1] %}
{%- set content = content.split('</think>')[-1] %}
{%- elif loop.index0 > ns.last_user_index and not (enable_thinking is defined and not enable_thinking) %}
{%- set reasoning_content = '' %}
{%- elif loop.index0 < ns.last_user_index and ns.has_thinking %}
{%- set reasoning_content = '' %}
{%- endif %}
{%- if ((clear_thinking is defined and not clear_thinking) or loop.index0 > ns.last_user_index) and reasoning_content is defined -%}
{{ '<think>' + reasoning_content + '</think>'}}
{%- else -%}
{{ '</think>' }}
{%- endif -%}
{%- if content.strip() -%}
{{ content.strip() }}
{%- endif -%}
{% if m.tool_calls %}
{% for tc in m.tool_calls %}
{%- if tc.function %}
{%- set tc = tc.function %}
{%- endif %}
{{- '<tool_call>' + tc.name -}}
{% set _args = tc.arguments %}{% for k, v in _args.items() %}<arg_key>{{ k }}</arg_key><arg_value>{{ v | tojson(ensure_ascii=False) if v is not string else v }}</arg_value>{% endfor %}</tool_call>{% endfor %}
{% endif %}
{%- elif m.role == 'tool' -%}
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
{{- '<|observation|>' -}}
{%- endif %}
{%- if m.content is string -%}
{{- '<tool_response>' + m.content + '</tool_response>' -}}
{%- elif m.content is iterable and m.content is not mapping and m.content and m.content.0.type == "tool_reference" -%}
{{- '<tool_response><tools>\n' -}}
{% for tr in m.content %}
{%- for tool in tools -%}
{%- if 'function' in tool -%}
{%- set tool = tool['function'] -%}
{%- endif -%}
{%- if tool.name == tr.name -%}
{{- tool_to_json(tool) + '\n' -}}
{%- endif -%}
{%- endfor -%}
{%- endfor -%}
{{- '</tools></tool_response>' -}}
{%- else -%}
{{- '<tool_response>' + visible_text(m.content) + '</tool_response>' -}}
{% endif -%}
{%- elif m.role == 'system' -%}
<|system|>{{ visible_text(m.content) }}
{%- endif -%}
{%- endfor -%}
{%- if add_generation_prompt -%}
<|assistant|>{{- '</think>' if (enable_thinking is defined and not enable_thinking) else '<think>' -}}
{%- endif -%} |