Text Generation
Transformers
Safetensors
PyTorch
nemotron_h
nvidia
nemotron-3
latent-moe
mtp
conversational
Eval Results
8-bit precision
modelopt
Instructions to use nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4") model = AutoModelForCausalLM.from_pretrained("nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4", 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]:])) - Inference
- HuggingChat
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4
- SGLang
How to use nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4 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 "nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4" \ --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": "nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4", "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 "nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4" \ --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": "nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4 with Docker Model Runner:
docker model run hf.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4
Add files using upload-large-folder tool
Browse files- .gitattributes +3 -0
- chat_template.jinja +195 -0
- hf_quant_config.json +0 -0
- model-00003-of-00113.json +20 -0
- model-00004-of-00113.json +0 -0
- model-00007-of-00113.json +20 -0
- model-00008-of-00113.json +14 -0
- model-00009-of-00113.json +0 -0
- model-00013-of-00113.json +0 -0
- model-00016-of-00113.json +0 -0
- model-00021-of-00113.json +20 -0
- model-00023-of-00113.json +20 -0
- model-00026-of-00113.json +20 -0
- model-00027-of-00113.json +0 -0
- model-00029-of-00113.json +0 -0
- model-00032-of-00113.json +20 -0
- model-00034-of-00113.json +0 -0
- model-00035-of-00113.json +20 -0
- model-00037-of-00113.json +20 -0
- model-00038-of-00113.json +0 -0
- model-00041-of-00113.json +0 -0
- model-00042-of-00113.json +20 -0
- model-00044-of-00113.json +20 -0
- model-00045-of-00113.json +0 -0
- model-00046-of-00113.json +20 -0
- model-00047-of-00113.json +0 -0
- model-00052-of-00113.json +0 -0
- model-00054-of-00113.json +0 -0
- model-00055-of-00113.json +20 -0
- model-00056-of-00113.json +0 -0
- model-00057-of-00113.json +20 -0
- model-00063-of-00113.json +0 -0
- model-00065-of-00113.json +14 -0
- model-00067-of-00113.json +20 -0
- model-00072-of-00113.json +0 -0
- model-00073-of-00113.json +20 -0
- model-00075-of-00113.json +0 -0
- model-00079-of-00113.json +0 -0
- model-00080-of-00113.json +20 -0
- model-00083-of-00113.json +14 -0
- model-00084-of-00113.json +0 -0
- model-00086-of-00113.json +0 -0
- model-00095-of-00113.json +0 -0
- model-00100-of-00113.json +0 -0
- model-00102-of-00113.json +0 -0
- model-00108-of-00113.json +0 -0
- model-00109-of-00113.json +228 -0
- model-00112-of-00113.json +245 -0
- special_tokens_map.json +30 -0
- ultra_v3_reasoning_parser.py +28 -0
.gitattributes
CHANGED
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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config.json filter=lfs diff=lfs merge=lfs -text
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model.safetensors.index.json filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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chat_template.jinja
ADDED
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@@ -0,0 +1,195 @@
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| 1 |
+
{% macro render_extra_keys(json_dict, handled_keys) %}
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| 2 |
+
{%- if json_dict is mapping %}
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| 3 |
+
{%- for json_key in json_dict if json_key not in handled_keys %}
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| 4 |
+
{%- if json_dict[json_key] is mapping or (json_dict[json_key] is sequence and json_dict[json_key] is not string) %}
|
| 5 |
+
{{- '\n<' ~ json_key ~ '>' ~ (json_dict[json_key] | tojson | safe) ~ '</' ~ json_key ~ '>' }}
|
| 6 |
+
{%- else %}
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| 7 |
+
{{-'\n<' ~ json_key ~ '>' ~ (json_dict[json_key] | string) ~ '</' ~ json_key ~ '>' }}
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| 8 |
+
{%- endif %}
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| 9 |
+
{%- endfor %}
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| 10 |
+
{%- endif %}
|
| 11 |
+
{% endmacro %}
|
| 12 |
+
{%- set enable_thinking = enable_thinking if enable_thinking is defined else True %}
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| 13 |
+
{%- set medium_effort = medium_effort if medium_effort is defined else False %}
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| 14 |
+
{%- set truncate_history_thinking = truncate_history_thinking if truncate_history_thinking is defined else True %}
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| 15 |
+
{%- set ns = namespace(last_user_idx = -1) %}
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| 16 |
+
{%- set loop_messages = messages %}
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| 17 |
+
{%- for m in loop_messages %}
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| 18 |
+
{%- if m["role"] == "user" %}
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| 19 |
+
{%- set ns.last_user_idx = loop.index0 %}
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| 20 |
+
{%- endif %}
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| 21 |
+
{%- endfor %}
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| 22 |
+
{%- if messages[0]["role"] == "system" %}
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| 23 |
+
{%- set system_message = messages[0]["content"] %}
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| 24 |
+
{%- set loop_messages = messages[1:] %}
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| 25 |
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{%- else %}
|
| 26 |
+
{%- set system_message = "" %}
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| 27 |
+
{%- set loop_messages = messages %}
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| 28 |
+
{%- endif %}
|
| 29 |
+
{%- if not tools is defined %}
|
| 30 |
+
{%- set tools = [] %}
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| 31 |
+
{%- endif %}
|
| 32 |
+
{%- set ns = namespace(last_user_idx = -1) %}
|
| 33 |
+
{%- for m in loop_messages %}
|
| 34 |
+
{%- if m["role"] == "user" %}
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| 35 |
+
{%- set ns.last_user_idx = loop.index0 %}
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| 36 |
+
{%- endif %}
|
| 37 |
+
{%- endfor %}
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| 38 |
+
{%- if system_message is defined %}
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| 39 |
+
{{- "<|im_start|>system\n" + system_message }}
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| 40 |
+
{%- else %}
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| 41 |
+
{%- if tools is iterable and tools | length > 0 %}
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| 42 |
+
{{- "<|im_start|>system\n" }}
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| 43 |
+
{%- endif %}
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| 44 |
+
{%- endif %}
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| 45 |
+
{%- if tools is iterable and tools | length > 0 %}
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| 46 |
+
{%- if system_message is defined and system_message | length > 0 %}
|
| 47 |
+
{{- "\n\n" }}
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| 48 |
+
{%- endif %}
|
| 49 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n" }}
|
| 50 |
+
{{- "<tools>" }}
|
| 51 |
+
{%- for tool in tools %}
|
| 52 |
+
{%- if tool.function is defined %}
|
| 53 |
+
{%- set tool = tool.function %}
|
| 54 |
+
{%- endif %}
|
| 55 |
+
{{- "\n<function>\n<name>" ~ tool.name ~ "</name>" }}
|
| 56 |
+
{%- if tool.description is defined %}
|
| 57 |
+
{{- '\n<description>' ~ (tool.description | trim) ~ '</description>' }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{{- '\n<parameters>' }}
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| 60 |
+
{%- if tool.parameters is defined and tool.parameters is mapping and tool.parameters.properties is defined and tool.parameters.properties is mapping %}
|
| 61 |
+
{%- for param_name, param_fields in tool.parameters.properties|items %}
|
| 62 |
+
{{- '\n<parameter>' }}
|
| 63 |
+
{{- '\n<name>' ~ param_name ~ '</name>' }}
|
| 64 |
+
{%- if param_fields.type is defined %}
|
| 65 |
+
{{- '\n<type>' ~ (param_fields.type | string) ~ '</type>' }}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- if param_fields.description is defined %}
|
| 68 |
+
{{- '\n<description>' ~ (param_fields.description | trim) ~ '</description>' }}
|
| 69 |
+
{%- endif %}
|
| 70 |
+
{%- if param_fields.enum is defined %}
|
| 71 |
+
{{- '\n<enum>' ~ (param_fields.enum | tojson | safe) ~ '</enum>' }}
|
| 72 |
+
{%- endif %}
|
| 73 |
+
{%- set handled_keys = ['name', 'type', 'description', 'enum'] %}
|
| 74 |
+
{{- render_extra_keys(param_fields, handled_keys) }}
|
| 75 |
+
{{- '\n</parameter>' }}
|
| 76 |
+
{%- endfor %}
|
| 77 |
+
{%- endif %}
|
| 78 |
+
{% set handled_keys = ['type', 'properties', 'required'] %}
|
| 79 |
+
{{- render_extra_keys(tool.parameters, handled_keys) }}
|
| 80 |
+
{%- if tool.parameters is defined and tool.parameters.required is defined %}
|
| 81 |
+
{{- '\n<required>' ~ (tool.parameters.required | tojson | safe) ~ '</required>' }}
|
| 82 |
+
{%- endif %}
|
| 83 |
+
{{- '\n</parameters>' }}
|
| 84 |
+
{%- set handled_keys = ['type', 'name', 'description', 'parameters'] %}
|
| 85 |
+
{{- render_extra_keys(tool, handled_keys) }}
|
| 86 |
+
{{- '\n</function>' }}
|
| 87 |
+
{%- endfor %}
|
| 88 |
+
{{- "\n</tools>" }}
|
| 89 |
+
{{- '\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>' }}
|
| 90 |
+
{%- endif %}
|
| 91 |
+
{%- if system_message is defined %}
|
| 92 |
+
{{- '<|im_end|>\n' }}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if tools is iterable and tools | length > 0 %}
|
| 95 |
+
{{- '<|im_end|>\n' }}
|
| 96 |
+
{%- endif %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- for message in loop_messages %}
|
| 99 |
+
{%- if message.role == "assistant" %}
|
| 100 |
+
{%- if message.reasoning_content is defined and message.reasoning_content is string and message.reasoning_content | trim | length > 0 %}
|
| 101 |
+
{%- set content = "<think>\n" ~ message.reasoning_content ~ "</think>" ~ (message.content | default('', true)) %}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{%- set content = message.content | default('', true) %}
|
| 104 |
+
{%- if content is string -%}
|
| 105 |
+
{%- if '<think>' not in content and '</think>' not in content -%}
|
| 106 |
+
{%- set content = "<think></think>" ~ content -%}
|
| 107 |
+
{%- endif -%}
|
| 108 |
+
{%- else -%}
|
| 109 |
+
{%- set content = content -%}
|
| 110 |
+
{%- endif -%}
|
| 111 |
+
{%- endif %}
|
| 112 |
+
{%- if message.tool_calls is defined and message.tool_calls is iterable and message.tool_calls | length > 0 %}
|
| 113 |
+
{{- '<|im_start|>assistant\n' }}
|
| 114 |
+
{%- set include_content = not (truncate_history_thinking and loop.index0 < ns.last_user_idx) %}
|
| 115 |
+
{%- if content is string and content | trim | length > 0 %}
|
| 116 |
+
{%- if include_content %}
|
| 117 |
+
{{- (content | trim) ~ '\n' -}}
|
| 118 |
+
{%- else %}
|
| 119 |
+
{%- set c = (content | string) %}
|
| 120 |
+
{%- if '</think>' in c %}
|
| 121 |
+
{%- set c = c.split('</think>')[-1] %}
|
| 122 |
+
{%- elif '<think>' in c %}
|
| 123 |
+
{%- set c = c.split('<think>')[0] %}
|
| 124 |
+
{%- endif %}
|
| 125 |
+
{%- set c = "<think></think>" ~ c %}
|
| 126 |
+
{%- if c | length > 0 %}
|
| 127 |
+
{{- c ~ '\n' -}}
|
| 128 |
+
{%- endif %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{%- else %}
|
| 131 |
+
{{- "<think></think>" -}}
|
| 132 |
+
{%- endif %}
|
| 133 |
+
{%- for tool_call in message.tool_calls %}
|
| 134 |
+
{%- if tool_call.function is defined %}
|
| 135 |
+
{%- set tool_call = tool_call.function %}
|
| 136 |
+
{%- endif %}
|
| 137 |
+
{{- '<tool_call>\n<function=' ~ tool_call.name ~ '>\n' -}}
|
| 138 |
+
{%- if tool_call.arguments is defined %}
|
| 139 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 140 |
+
{{- '<parameter=' ~ args_name ~ '>\n' -}}
|
| 141 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 142 |
+
{{- args_value ~ '\n</parameter>\n' -}}
|
| 143 |
+
{%- endfor %}
|
| 144 |
+
{%- endif %}
|
| 145 |
+
{{- '</function>\n</tool_call>\n' -}}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{{- '<|im_end|>\n' }}
|
| 148 |
+
{%- else %}
|
| 149 |
+
{%- if not (truncate_history_thinking and loop.index0 < ns.last_user_idx) %}
|
| 150 |
+
{{- '<|im_start|>assistant\n' ~ (content | default('', true) | string | trim) ~ '<|im_end|>\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{%- set c = (content | default('', true) | string) %}
|
| 153 |
+
{%- if '<think>' in c and '</think>' in c %}
|
| 154 |
+
{%- set c = "<think></think>" ~ c.split('</think>')[-1] %}
|
| 155 |
+
{%- endif %}
|
| 156 |
+
{%- set c = c | trim %}
|
| 157 |
+
{%- if c | length > 0 %}
|
| 158 |
+
{{- '<|im_start|>assistant\n' ~ c ~ '<|im_end|>\n' }}
|
| 159 |
+
{%- else %}
|
| 160 |
+
{{- '<|im_start|>assistant\n<|im_end|>\n' }}
|
| 161 |
+
{%- endif %}
|
| 162 |
+
{%- endif %}
|
| 163 |
+
{%- endif %}
|
| 164 |
+
{%- elif message.role == "user" or message.role == "system" %}
|
| 165 |
+
{{- '<|im_start|>' + message.role + '\n' }}
|
| 166 |
+
{%- set content = message.content | string %}
|
| 167 |
+
{%- if message.role == "user" and loop.index0 == ns.last_user_idx and medium_effort %}
|
| 168 |
+
{{- content + '\n\n{reasoning effort: efficient}' }}
|
| 169 |
+
{%- else %}
|
| 170 |
+
{{- content }}
|
| 171 |
+
{%- endif %}
|
| 172 |
+
{{- '<|im_end|>\n' }}
|
| 173 |
+
{%- elif message.role == "tool" %}
|
| 174 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 175 |
+
{{- '<|im_start|>user\n' }}
|
| 176 |
+
{%- endif %}
|
| 177 |
+
{{- '<tool_response>\n' }}
|
| 178 |
+
{{- message.content }}
|
| 179 |
+
{{- '\n</tool_response>\n' }}
|
| 180 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 181 |
+
{{- '<|im_end|>\n' }}
|
| 182 |
+
{%- elif loop.last %}
|
| 183 |
+
{{- '<|im_end|>\n' }}
|
| 184 |
+
{%- endif %}
|
| 185 |
+
{%- else %}
|
| 186 |
+
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>\n' }}
|
| 187 |
+
{%- endif %}
|
| 188 |
+
{%- endfor %}
|
| 189 |
+
{%- if add_generation_prompt %}
|
| 190 |
+
{%- if enable_thinking %}
|
| 191 |
+
{{- '<|im_start|>assistant\n<think>\n' }}
|
| 192 |
+
{%- else %}
|
| 193 |
+
{{- '<|im_start|>assistant\n<think></think>' }}
|
| 194 |
+
{%- endif %}
|
| 195 |
+
{%- endif %}
|
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model-00003-of-00113.json
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|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 421762576
|
| 4 |
+
},
|
| 5 |
+
"weight_map": {
|
| 6 |
+
"backbone.layers.2.mixer.in_proj.input_scale": "model-00003-of-00113.safetensors",
|
| 7 |
+
"backbone.layers.2.mixer.in_proj.weight_scale": "model-00003-of-00113.safetensors",
|
| 8 |
+
"backbone.layers.2.mixer.out_proj.input_scale": "model-00003-of-00113.safetensors",
|
| 9 |
+
"backbone.layers.2.mixer.out_proj.weight_scale": "model-00003-of-00113.safetensors",
|
| 10 |
+
"backbone.layers.2.mixer.A_log": "model-00003-of-00113.safetensors",
|
| 11 |
+
"backbone.layers.2.mixer.D": "model-00003-of-00113.safetensors",
|
| 12 |
+
"backbone.layers.2.mixer.conv1d.bias": "model-00003-of-00113.safetensors",
|
| 13 |
+
"backbone.layers.2.mixer.conv1d.weight": "model-00003-of-00113.safetensors",
|
| 14 |
+
"backbone.layers.2.mixer.dt_bias": "model-00003-of-00113.safetensors",
|
| 15 |
+
"backbone.layers.2.mixer.norm.weight": "model-00003-of-00113.safetensors",
|
| 16 |
+
"backbone.layers.2.norm.weight": "model-00003-of-00113.safetensors",
|
| 17 |
+
"backbone.layers.2.mixer.in_proj.weight": "model-00003-of-00113.safetensors",
|
| 18 |
+
"backbone.layers.2.mixer.out_proj.weight": "model-00003-of-00113.safetensors"
|
| 19 |
+
}
|
| 20 |
+
}
|
model-00004-of-00113.json
ADDED
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model-00007-of-00113.json
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|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 421762576
|
| 4 |
+
},
|
| 5 |
+
"weight_map": {
|
| 6 |
+
"backbone.layers.6.mixer.in_proj.input_scale": "model-00007-of-00113.safetensors",
|
| 7 |
+
"backbone.layers.6.mixer.in_proj.weight_scale": "model-00007-of-00113.safetensors",
|
| 8 |
+
"backbone.layers.6.mixer.out_proj.input_scale": "model-00007-of-00113.safetensors",
|
| 9 |
+
"backbone.layers.6.mixer.out_proj.weight_scale": "model-00007-of-00113.safetensors",
|
| 10 |
+
"backbone.layers.6.mixer.A_log": "model-00007-of-00113.safetensors",
|
| 11 |
+
"backbone.layers.6.mixer.D": "model-00007-of-00113.safetensors",
|
| 12 |
+
"backbone.layers.6.mixer.conv1d.bias": "model-00007-of-00113.safetensors",
|
| 13 |
+
"backbone.layers.6.mixer.conv1d.weight": "model-00007-of-00113.safetensors",
|
| 14 |
+
"backbone.layers.6.mixer.dt_bias": "model-00007-of-00113.safetensors",
|
| 15 |
+
"backbone.layers.6.mixer.norm.weight": "model-00007-of-00113.safetensors",
|
| 16 |
+
"backbone.layers.6.norm.weight": "model-00007-of-00113.safetensors",
|
| 17 |
+
"backbone.layers.6.mixer.in_proj.weight": "model-00007-of-00113.safetensors",
|
| 18 |
+
"backbone.layers.6.mixer.out_proj.weight": "model-00007-of-00113.safetensors"
|
| 19 |
+
}
|
| 20 |
+
}
|
model-00008-of-00113.json
ADDED
|
@@ -0,0 +1,14 @@
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|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 276840456
|
| 4 |
+
},
|
| 5 |
+
"weight_map": {
|
| 6 |
+
"backbone.layers.7.mixer.k_proj.k_scale": "model-00008-of-00113.safetensors",
|
| 7 |
+
"backbone.layers.7.mixer.v_proj.v_scale": "model-00008-of-00113.safetensors",
|
| 8 |
+
"backbone.layers.7.mixer.k_proj.weight": "model-00008-of-00113.safetensors",
|
| 9 |
+
"backbone.layers.7.mixer.o_proj.weight": "model-00008-of-00113.safetensors",
|
| 10 |
+
"backbone.layers.7.mixer.q_proj.weight": "model-00008-of-00113.safetensors",
|
| 11 |
+
"backbone.layers.7.mixer.v_proj.weight": "model-00008-of-00113.safetensors",
|
| 12 |
+
"backbone.layers.7.norm.weight": "model-00008-of-00113.safetensors"
|
| 13 |
+
}
|
| 14 |
+
}
|
model-00009-of-00113.json
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model-00013-of-00113.json
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model-00016-of-00113.json
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model-00021-of-00113.json
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|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 421762576
|
| 4 |
+
},
|
| 5 |
+
"weight_map": {
|
| 6 |
+
"backbone.layers.20.mixer.in_proj.input_scale": "model-00021-of-00113.safetensors",
|
| 7 |
+
"backbone.layers.20.mixer.in_proj.weight_scale": "model-00021-of-00113.safetensors",
|
| 8 |
+
"backbone.layers.20.mixer.out_proj.input_scale": "model-00021-of-00113.safetensors",
|
| 9 |
+
"backbone.layers.20.mixer.out_proj.weight_scale": "model-00021-of-00113.safetensors",
|
| 10 |
+
"backbone.layers.20.mixer.A_log": "model-00021-of-00113.safetensors",
|
| 11 |
+
"backbone.layers.20.mixer.D": "model-00021-of-00113.safetensors",
|
| 12 |
+
"backbone.layers.20.mixer.conv1d.bias": "model-00021-of-00113.safetensors",
|
| 13 |
+
"backbone.layers.20.mixer.conv1d.weight": "model-00021-of-00113.safetensors",
|
| 14 |
+
"backbone.layers.20.mixer.dt_bias": "model-00021-of-00113.safetensors",
|
| 15 |
+
"backbone.layers.20.mixer.norm.weight": "model-00021-of-00113.safetensors",
|
| 16 |
+
"backbone.layers.20.norm.weight": "model-00021-of-00113.safetensors",
|
| 17 |
+
"backbone.layers.20.mixer.in_proj.weight": "model-00021-of-00113.safetensors",
|
| 18 |
+
"backbone.layers.20.mixer.out_proj.weight": "model-00021-of-00113.safetensors"
|
| 19 |
+
}
|
| 20 |
+
}
|
model-00023-of-00113.json
ADDED
|
@@ -0,0 +1,20 @@
|
|
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|
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|
|
|
|
|
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|
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|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 421762576
|
| 4 |
+
},
|
| 5 |
+
"weight_map": {
|
| 6 |
+
"backbone.layers.22.mixer.in_proj.input_scale": "model-00023-of-00113.safetensors",
|
| 7 |
+
"backbone.layers.22.mixer.in_proj.weight_scale": "model-00023-of-00113.safetensors",
|
| 8 |
+
"backbone.layers.22.mixer.out_proj.input_scale": "model-00023-of-00113.safetensors",
|
| 9 |
+
"backbone.layers.22.mixer.out_proj.weight_scale": "model-00023-of-00113.safetensors",
|
| 10 |
+
"backbone.layers.22.mixer.A_log": "model-00023-of-00113.safetensors",
|
| 11 |
+
"backbone.layers.22.mixer.D": "model-00023-of-00113.safetensors",
|
| 12 |
+
"backbone.layers.22.mixer.conv1d.bias": "model-00023-of-00113.safetensors",
|
| 13 |
+
"backbone.layers.22.mixer.conv1d.weight": "model-00023-of-00113.safetensors",
|
| 14 |
+
"backbone.layers.22.mixer.dt_bias": "model-00023-of-00113.safetensors",
|
| 15 |
+
"backbone.layers.22.mixer.norm.weight": "model-00023-of-00113.safetensors",
|
| 16 |
+
"backbone.layers.22.norm.weight": "model-00023-of-00113.safetensors",
|
| 17 |
+
"backbone.layers.22.mixer.in_proj.weight": "model-00023-of-00113.safetensors",
|
| 18 |
+
"backbone.layers.22.mixer.out_proj.weight": "model-00023-of-00113.safetensors"
|
| 19 |
+
}
|
| 20 |
+
}
|
model-00026-of-00113.json
ADDED
|
@@ -0,0 +1,20 @@
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|
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|
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|
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|
|
|
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|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 421762576
|
| 4 |
+
},
|
| 5 |
+
"weight_map": {
|
| 6 |
+
"backbone.layers.25.mixer.in_proj.input_scale": "model-00026-of-00113.safetensors",
|
| 7 |
+
"backbone.layers.25.mixer.in_proj.weight_scale": "model-00026-of-00113.safetensors",
|
| 8 |
+
"backbone.layers.25.mixer.out_proj.input_scale": "model-00026-of-00113.safetensors",
|
| 9 |
+
"backbone.layers.25.mixer.out_proj.weight_scale": "model-00026-of-00113.safetensors",
|
| 10 |
+
"backbone.layers.25.mixer.A_log": "model-00026-of-00113.safetensors",
|
| 11 |
+
"backbone.layers.25.mixer.D": "model-00026-of-00113.safetensors",
|
| 12 |
+
"backbone.layers.25.mixer.conv1d.bias": "model-00026-of-00113.safetensors",
|
| 13 |
+
"backbone.layers.25.mixer.conv1d.weight": "model-00026-of-00113.safetensors",
|
| 14 |
+
"backbone.layers.25.mixer.dt_bias": "model-00026-of-00113.safetensors",
|
| 15 |
+
"backbone.layers.25.mixer.norm.weight": "model-00026-of-00113.safetensors",
|
| 16 |
+
"backbone.layers.25.norm.weight": "model-00026-of-00113.safetensors",
|
| 17 |
+
"backbone.layers.25.mixer.in_proj.weight": "model-00026-of-00113.safetensors",
|
| 18 |
+
"backbone.layers.25.mixer.out_proj.weight": "model-00026-of-00113.safetensors"
|
| 19 |
+
}
|
| 20 |
+
}
|
model-00027-of-00113.json
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model-00029-of-00113.json
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model-00032-of-00113.json
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 421762576
|
| 4 |
+
},
|
| 5 |
+
"weight_map": {
|
| 6 |
+
"backbone.layers.31.mixer.in_proj.input_scale": "model-00032-of-00113.safetensors",
|
| 7 |
+
"backbone.layers.31.mixer.in_proj.weight_scale": "model-00032-of-00113.safetensors",
|
| 8 |
+
"backbone.layers.31.mixer.out_proj.input_scale": "model-00032-of-00113.safetensors",
|
| 9 |
+
"backbone.layers.31.mixer.out_proj.weight_scale": "model-00032-of-00113.safetensors",
|
| 10 |
+
"backbone.layers.31.mixer.A_log": "model-00032-of-00113.safetensors",
|
| 11 |
+
"backbone.layers.31.mixer.D": "model-00032-of-00113.safetensors",
|
| 12 |
+
"backbone.layers.31.mixer.conv1d.bias": "model-00032-of-00113.safetensors",
|
| 13 |
+
"backbone.layers.31.mixer.conv1d.weight": "model-00032-of-00113.safetensors",
|
| 14 |
+
"backbone.layers.31.mixer.dt_bias": "model-00032-of-00113.safetensors",
|
| 15 |
+
"backbone.layers.31.mixer.norm.weight": "model-00032-of-00113.safetensors",
|
| 16 |
+
"backbone.layers.31.norm.weight": "model-00032-of-00113.safetensors",
|
| 17 |
+
"backbone.layers.31.mixer.in_proj.weight": "model-00032-of-00113.safetensors",
|
| 18 |
+
"backbone.layers.31.mixer.out_proj.weight": "model-00032-of-00113.safetensors"
|
| 19 |
+
}
|
| 20 |
+
}
|
model-00034-of-00113.json
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model-00035-of-00113.json
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|
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|
|
|
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|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 421762576
|
| 4 |
+
},
|
| 5 |
+
"weight_map": {
|
| 6 |
+
"backbone.layers.34.mixer.in_proj.input_scale": "model-00035-of-00113.safetensors",
|
| 7 |
+
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"metadata": {
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"total_size": 421762576
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{
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|
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|
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|
| 204 |
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|
| 205 |
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|
| 206 |
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|
| 207 |
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|
| 208 |
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|
| 209 |
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|
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|
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|
| 214 |
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|
| 215 |
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|
| 216 |
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|
| 217 |
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|
| 218 |
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|
| 219 |
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|
| 220 |
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|
| 221 |
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|
| 222 |
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|
| 223 |
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|
| 224 |
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|
| 225 |
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|
| 226 |
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|
| 227 |
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|
| 228 |
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|
| 229 |
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|
| 230 |
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|
| 231 |
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|
| 232 |
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|
| 233 |
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|
| 234 |
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|
| 235 |
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|
| 236 |
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"mtp.layers.1.mixer.experts.511.down_proj.weight": "model-00112-of-00113.safetensors",
|
| 237 |
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|
| 238 |
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|
| 239 |
+
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|
| 240 |
+
"mtp.layers.1.mixer.experts.53.down_proj.weight": "model-00112-of-00113.safetensors",
|
| 241 |
+
"mtp.layers.1.mixer.experts.53.up_proj.weight": "model-00112-of-00113.safetensors",
|
| 242 |
+
"mtp.layers.1.mixer.experts.54.down_proj.weight": "model-00112-of-00113.safetensors",
|
| 243 |
+
"mtp.layers.1.mixer.experts.54.up_proj.weight": "model-00112-of-00113.safetensors"
|
| 244 |
+
}
|
| 245 |
+
}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,30 @@
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": {
|
| 3 |
+
"content": "<s>",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"eos_token": {
|
| 10 |
+
"content": "<|im_end|>",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"pad_token": {
|
| 17 |
+
"content": "<|im_end|>",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"single_word": false
|
| 22 |
+
},
|
| 23 |
+
"unk_token": {
|
| 24 |
+
"content": "<unk>",
|
| 25 |
+
"lstrip": false,
|
| 26 |
+
"normalized": false,
|
| 27 |
+
"rstrip": false,
|
| 28 |
+
"single_word": false
|
| 29 |
+
}
|
| 30 |
+
}
|
ultra_v3_reasoning_parser.py
ADDED
|
@@ -0,0 +1,28 @@
|
|
|
|
|
|
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|
|
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|
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|
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|
|
|
|
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|
|
|
|
| 1 |
+
from vllm.reasoning.abs_reasoning_parsers import ReasoningParserManager
|
| 2 |
+
from vllm.reasoning.deepseek_r1_reasoning_parser import DeepSeekR1ReasoningParser
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
@ReasoningParserManager.register_module("ultra_v3")
|
| 6 |
+
class UltraV3ReasoningParser(DeepSeekR1ReasoningParser):
|
| 7 |
+
def extract_reasoning(self, model_output, request):
|
| 8 |
+
reasoning_content, final_content = super().extract_reasoning(
|
| 9 |
+
model_output, request
|
| 10 |
+
)
|
| 11 |
+
if (
|
| 12 |
+
hasattr(request, "chat_template_kwargs")
|
| 13 |
+
and request.chat_template_kwargs
|
| 14 |
+
and (
|
| 15 |
+
request.chat_template_kwargs.get("enable_thinking") is False
|
| 16 |
+
or request.chat_template_kwargs.get("force_nonempty_content") is True
|
| 17 |
+
)
|
| 18 |
+
and final_content is None
|
| 19 |
+
):
|
| 20 |
+
"""
|
| 21 |
+
The original `deepseek_r1` reasoning parser this inherits from will automatically put everything in the reasoning content when it cannot parse out reasoning. This was fine for the DeepSeek R1 model that was not intended to be used without reasoning.
|
| 22 |
+
1. Since the Nemotron 3 Nano and Super both have thinking off modes modulated by "enable_thinking=false" in the chat template kwargs, this change instead which will properly place the content in cases where there is no thinking enabled via config.
|
| 23 |
+
2. There are rare cases where the model will output only reasoning without an end-think token `</think>` (e.g. reasoning exceeds max length), which results in empty content returned. End users may want to unilaterally avoid such cases and always have a content response even if the model does not finish its reasoning.
|
| 24 |
+
"""
|
| 25 |
+
# Put all nonempty content into the content, rather than return content
|
| 26 |
+
reasoning_content, final_content = None, reasoning_content
|
| 27 |
+
|
| 28 |
+
return reasoning_content, final_content
|