GLM-5 · Tokenizer · OpenModelAtlas

Tokenizer

no parameterschat_template.jinja

Encode each prompt as a sequence of token IDs.

out: $I$ [B batch, T positions]

Explanation

Chat prompts are wrapped in the checkpoint’s chat template, which opens with [gMASK]<sop> and marks each message with its role. Token IDs index a vocabulary of 154,880 entries; $T$ counts the tokens.

Codetokenizer_config.json 1–33 · 2 more files

tokenizer_config.json 1–33

{
  "backend": "tokenizers",
  "clean_up_tokenization_spaces": false,
  "do_lower_case": false,
  "eos_token": "<|endoftext|>",
  "extra_special_tokens": [
    "<|endoftext|>",
    "[MASK]",
    "[gMASK]",
    "[sMASK]",
    "<sop>",
    "<eop>",
    "<|system|>",
    "<|user|>",
    "<|assistant|>",
    "<|observation|>",
    "<|begin_of_image|>",
    "<|end_of_image|>",
    "<|begin_of_video|>",
    "<|end_of_video|>",
    "<|begin_of_audio|>",
    "<|end_of_audio|>",
    "<|begin_of_transcription|>",
    "<|end_of_transcription|>"
  ],
  "is_local": true,
  "model_max_length": 202752,
  "model_specific_special_tokens": {},
  "pad_token": "<|endoftext|>",
  "padding_side": "left",
  "remove_space": false,
  "tokenizer_class": "TokenizersBackend"
}

chat_template.jinja 1

[gMASK]<sop>

chat_template.jinja 38–41

{%- for m in messages -%}
{%- if m.role == 'user' -%}<|user|>{{ visible_text(m.content) }}
{%- elif m.role == 'assistant' -%}
<|assistant|>

chat_template.jinja 68–86

{%- elif m.role == 'tool' -%}
{%- if m.content is string -%}
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
    {{- '<|observation|>' }}
{%- endif %}
{{- '<tool_response>' }}
{{- m.content }}
{{- '</tool_response>' }}
{%- else -%}
<|observation|>{% for tr in m.content %}
<tool_response>{{ tr.output if tr.output is defined else tr }}</tool_response>{% endfor -%}
{% 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 -%}

config.json 1–59

{
  "architectures": [
    "GlmMoeDsaForCausalLM"
  ],
  "attention_bias": false,
  "attention_dropout": 0.0,
  "dtype": "bfloat16",
  "eos_token_id": [
    154820,
    154827,
    154829
  ],
  "ep_size": 1,
  "first_k_dense_replace": 3,
  "hidden_act": "silu",
  "head_dim": 64,
  "hidden_size": 6144,
  "index_head_dim": 128,
  "index_n_heads": 32,
  "index_topk": 2048,
  "indexer_rope_interleave": true,
  "initializer_range": 0.02,
  "intermediate_size": 12288,
  "kv_lora_rank": 512,
  "max_position_embeddings": 202752,
  "moe_intermediate_size": 2048,
  "moe_layer_freq": 1,
  "model_type": "glm_moe_dsa",
  "n_group": 1,
  "n_routed_experts": 256,
  "n_shared_experts": 1,
  "norm_topk_prob": true,
  "num_attention_heads": 64,
  "num_experts_per_tok": 8,
  "num_hidden_layers": 78,
  "num_key_value_heads": 64,
  "num_nextn_predict_layers": 1,
  "pad_token_id": 154820,
  "pretraining_tp": 1,
  "q_lora_rank": 2048,
  "qk_head_dim": 256,
  "qk_nope_head_dim": 192,
  "qk_rope_head_dim": 64,
  "rms_norm_eps": 1e-05,
  "rope_interleave": true,
  "rope_parameters": {
    "rope_theta": 1000000,
    "rope_type": "default"
  },
  "routed_scaling_factor": 2.5,
  "scoring_func": "sigmoid",
  "tie_word_embeddings": false,
  "topk_group": 1,
  "topk_method": "noaux_tc",
  "transformers_version": "5.0.2.dev0",
  "use_cache": true,
  "v_head_dim": 256,
  "vocab_size": 154880
}

Sources3

Direct evidence

The checkpoint’s tokenizer is a Hugging Face tokenizers file (tokenizer.json) loaded by the generic TokenizersBackend; the configuration declares its special tokens, among them the role markers and [gMASK] and <sop>.

tokenizer · zai-org/GLM-5 / tokenizer_config.json
Pinned revision c183ef8c61fa ↗ · lines 1–33

Read code excerpt

{
  "backend": "tokenizers",
  "clean_up_tokenization_spaces": false,
  "do_lower_case": false,
  "eos_token": "<|endoftext|>",
  "extra_special_tokens": [
    "<|endoftext|>",
    "[MASK]",
    "[gMASK]",
    "[sMASK]",
    "<sop>",
    "<eop>",
    "<|system|>",
    "<|user|>",
    "<|assistant|>",
    "<|observation|>",
    "<|begin_of_image|>",
    "<|end_of_image|>",
    "<|begin_of_video|>",
    "<|end_of_video|>",
    "<|begin_of_audio|>",
    "<|end_of_audio|>",
    "<|begin_of_transcription|>",
    "<|end_of_transcription|>"
  ],
  "is_local": true,
  "model_max_length": 202752,
  "model_specific_special_tokens": {},
  "pad_token": "<|endoftext|>",
  "padding_side": "left",
  "remove_space": false,
  "tokenizer_class": "TokenizersBackend"
}

Direct evidence

chat-template · zai-org/GLM-5 / chat_template.jinja
Pinned revision c183ef8c61fa ↗ · lines 1–86

Read code excerpt

[gMASK]<sop>

… lines 2–37 omitted …

{%- for m in messages -%}
{%- if m.role == 'user' -%}<|user|>{{ visible_text(m.content) }}
{%- elif m.role == 'assistant' -%}
<|assistant|>

… lines 42–67 omitted …

{%- elif m.role == 'tool' -%}
{%- if m.content is string -%}
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
    {{- '<|observation|>' }}
{%- endif %}
{{- '<tool_response>' }}
{{- m.content }}
{{- '</tool_response>' }}
{%- else -%}
<|observation|>{% for tr in m.content %}
<tool_response>{{ tr.output if tr.output is defined else tr }}</tool_response>{% endfor -%}
{% 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 -%}

Direct evidence

The released configuration: width, 78 layers of which 3 dense, 64 heads, 256 routed experts and one shared, routing (sigmoid scores, one expert group, top-8, route scale 2.5), MLA ranks and head widths, the indexer (32 heads of 128, top 2,048, interleaved RoPE), vocabulary, default RoPE with θ = 1,000,000, and one multi-token-prediction layer.

config · zai-org/GLM-5 / config.json
Pinned revision c183ef8c61fa ↗ · lines 1–59

Read code excerpt

{
  "architectures": [
    "GlmMoeDsaForCausalLM"
  ],
  "attention_bias": false,
  "attention_dropout": 0.0,
  "dtype": "bfloat16",
  "eos_token_id": [
    154820,
    154827,
    154829
  ],
  "ep_size": 1,
  "first_k_dense_replace": 3,
  "hidden_act": "silu",
  "head_dim": 64,
  "hidden_size": 6144,
  "index_head_dim": 128,
  "index_n_heads": 32,
  "index_topk": 2048,
  "indexer_rope_interleave": true,
  "initializer_range": 0.02,
  "intermediate_size": 12288,
  "kv_lora_rank": 512,
  "max_position_embeddings": 202752,
  "moe_intermediate_size": 2048,
  "moe_layer_freq": 1,
  "model_type": "glm_moe_dsa",
  "n_group": 1,
  "n_routed_experts": 256,
  "n_shared_experts": 1,
  "norm_topk_prob": true,
  "num_attention_heads": 64,
  "num_experts_per_tok": 8,
  "num_hidden_layers": 78,
  "num_key_value_heads": 64,
  "num_nextn_predict_layers": 1,
  "pad_token_id": 154820,
  "pretraining_tp": 1,
  "q_lora_rank": 2048,
  "qk_head_dim": 256,
  "qk_nope_head_dim": 192,
  "qk_rope_head_dim": 64,
  "rms_norm_eps": 1e-05,
  "rope_interleave": true,
  "rope_parameters": {
    "rope_theta": 1000000,
    "rope_type": "default"
  },
  "routed_scaling_factor": 2.5,
  "scoring_func": "sigmoid",
  "tie_word_embeddings": false,
  "topk_group": 1,
  "topk_method": "noaux_tc",
  "transformers_version": "5.0.2.dev0",
  "use_cache": true,
  "v_head_dim": 256,
  "vocab_size": 154880
}