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Model: ylm-ai/ylm-1b
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---
tags:
- trl
- grpo
- gguf
base_model:
- openbmb/MiniCPM5-1B
---
# YLM-1B
YLM-1B is ylm-ai's first generation of MiniCPM5-based 1 billion parameter reasoning models. This model excels at reasoning, and features an internal scratchpad to solve problems.
This repository hosts the raw, original fp16 weights of YLM-1B, alongside llama.cpp-compatible GGUF files.
## Training Details
YLM-1B was trained with reinforcement learning to solve problems. The base model is MiniCPM5.
## Downloads
**q4_0 GGUF**: 600MB (for the desperate), click [here](https://huggingface.co/ylm-ai/ylm-1b/resolve/main/ylm-1b-q4_0.gguf?download=true)
**q8_0 GGUF**: 1.2 GB (good quality), click [here](https://huggingface.co/ylm-ai/ylm-1b/resolve/main/ylm-1b-q8_0.gguf?download=true)
**f16 GGUF**: 2.2 GB (exceptional quality), click [here](https://huggingface.co/ylm-ai/ylm-1b/resolve/main/ylm-1b-f16.gguf?download=true)
**HF Transformers**: 2.2 GB, [safetensors](https://huggingface.co/ylm-ai/ylm-1b/resolve/main/model.safetensors?download=true) [tokenizer.json](https://huggingface.co/ylm-ai/ylm-1b/resolve/main/tokenizer.json?download=true) [tokenizer_config.json](https://huggingface.co/ylm-ai/ylm-1b/resolve/main/tokenizer_config.json?download=true) [generation_config.json](https://huggingface.co/ylm-ai/ylm-1b/resolve/main/generation_config.json?download=true) [config.json](https://huggingface.co/ylm-ai/ylm-1b/resolve/main/config.json?download=true) [chat_template.jinja](https://huggingface.co/ylm-ai/ylm-1b/resolve/main/chat_template.jinja?download=true)

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{{- bos_token }}{%- if tools %}
{%- set tool_definitions %}
{{- "# Tools\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
{%- for tool in tools %}
{{- "\n" }}
{{- tool | tojson(ensure_ascii=False) }}
{%- endfor %}
{{- '\n</tools>\n\nTool usage guidelines:\n- You may call zero or more functions. If no function calls are needed, just answer normally and do not include any <function ... </function>.\n- When calling a function, return an XML object within <function ... </function> using:\n<function name="function-name"><param name="param-name">param-value</param></function>\n- param-value may be multi-line. If it contains <, & or newline characters, wrap it in a CDATA block: <param name="param-name"><![CDATA[...multi-line value...]]></param>' }}
{%- endset %}
{{- '<|im_start|>system\n' }}
{%- if messages[0].role == 'system' %}
{%- if '<tool_def_sep>' in messages[0].content %}
{{- messages[0].content.replace('<tool_def_sep>', tool_definitions) }}
{%- else %}
{{- messages[0].content + '\n\n' + tool_definitions }}
{%- endif %}
{%- else %}
{{- tool_definitions.lstrip() }}
{%- endif %}
{{- '<|im_end|>\n' }}
{%- else %}
{%- if messages[0].role == 'system' %}
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
{%- endif %}
{%- 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") or (message.role == "system" and not loop.first) %}
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
{%- elif message.role == "assistant" %}
{%- set reasoning_content = '' %}
{%- if message.reasoning_content is string %}
{%- set reasoning_content = message.reasoning_content %}
{%- 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 message.tool_calls %}
{%- set content_parts = content.split('<tool_sep>') %}
{%- set processed_content = content_parts[0] %}
{%- set tool_calls_count = message.tool_calls|length %}
{%- set tool_sep_count = content_parts|length - 1 %}
{%- set min_count = [tool_calls_count, tool_sep_count]|min %}
{%- for i in range(1, content_parts|length) %}
{%- set tool_index = i - 1 %}
{%- if tool_index < tool_calls_count %}
{%- set tool_call = message.tool_calls[tool_index] %}
{%- if tool_call.function %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{%- set single_tool_xml %}
{{- '<function name="' ~ tool_call.name ~ '">' }}
{%- if tool_call.arguments %}
{%- set args_dict = tool_call.arguments %}
{%- for param_name, param_value in args_dict.items() %}
{{- '<param name="' ~ param_name ~ '">' }}
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
{{- '<![CDATA[' + param_value + ']]>' }}
{%- else %}
{{- param_value }}
{%- endif %}
{{- '</param>' }}
{%- endfor %}
{%- endif %}
{{- '</function>' }}
{%- endset %}
{%- set processed_content = processed_content + single_tool_xml + content_parts[i] %}
{%- else %}
{%- set processed_content = processed_content + content_parts[i] %}
{%- endif %}
{%- endfor %}
{%- if tool_calls_count > tool_sep_count %}
{%- for remaining_index in range(tool_sep_count, tool_calls_count) %}
{%- set tool_call = message.tool_calls[remaining_index] %}
{%- if tool_call.function %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{%- set remaining_tool_xml %}
{{- '<function name="' ~ tool_call.name ~ '">' }}
{%- if tool_call.arguments %}
{%- set args_dict = tool_call.arguments %}
{%- for param_name, param_value in args_dict.items() %}
{{- '<param name="' ~ param_name ~ '">' }}
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
{{- '<![CDATA[' + param_value + ']]>' }}
{%- else %}
{{- param_value }}
{%- endif %}
{{- '</param>' }}
{%- endfor %}
{%- endif %}
{{- '</function>' }}
{%- endset %}
{%- set processed_content = processed_content + remaining_tool_xml %}
{%- endfor %}
{%- endif %}
{%- set content = processed_content %}
{%- endif %}
{%- if loop.index0 > ns.last_query_index %}
{%- if reasoning_content %}
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
{%- else %}
{{- '<|im_start|>' + message.role + '\n' + content }}
{%- endif %}
{%- else %}
{{- '<|im_start|>' + message.role + '\n' + content }}
{%- endif %}
{%- if message.tool_calls and not has_tool_sep %}
{%- for tool_call in message.tool_calls %}
{%- if (loop.first and content) or (not loop.first) %}
{{- '\n' }}
{%- endif %}
{%- if tool_call.function %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{- '<function name="' ~ tool_call.name ~ '">' }}
{%- if tool_call.arguments %}
{%- set args_dict = tool_call.arguments %}
{%- for param_name, param_value in args_dict.items() %}
{{- '<param name="' ~ param_name ~ '">' }}
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
{{- '<![CDATA[' + param_value + ']]>' }}
{%- else %}
{{- param_value }}
{%- endif %}
{{- '</param>' }}
{%- endfor %}
{%- endif %}
{{- '</function>' }}
{%- endfor %}
{%- endif %}
{{- '<|im_end|>\n' }}
{%- elif message.role == "tool" %}
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
{{- '<|im_start|>user' }}
{%- endif %}
{{- '\n<tool_response>\n' }}
{%- if message.content is string %}
{{- content }}
{%- else %}
{{- message.content | tojson(ensure_ascii=False) }}
{%- endif %}
{{- '\n</tool_response>' }}
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
{{- '<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
{%- if enable_thinking is defined %}
{%- if enable_thinking is false %}
{{- '<think>\n\n</think>\n\n' }}
{%- elif enable_thinking is true %}
{{- '<think>\n' }}
{%- endif %}
{%- endif %}
{%- endif %}

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{
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 0,
"dtype": "bfloat16",
"eos_token_id": 1,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 1536,
"initializer_range": 0.02,
"intermediate_size": 4608,
"max_position_embeddings": 131072,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 16,
"num_hidden_layers": 24,
"num_key_value_heads": 2,
"pad_token_id": 1,
"pretraining_tp": 1,
"rms_norm_eps": 1e-06,
"rope_parameters": {
"rope_theta": 5000000,
"rope_type": "default"
},
"tie_word_embeddings": false,
"transformers_version": "5.13.1",
"use_cache": false,
"vocab_size": 130560
}

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{
"_from_model_config": true,
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"do_sample": true,
"eos_token_id": [
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"pad_token_id": 1,
"temperature": 0.9,
"top_p": 0.95,
"transformers_version": "5.13.1"
}

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