DeepSeek-V3.2-Exp · Tokenizer

Tokenizer

no parameterstokenizer.apply_chat_template

Encode each prompt as a sequence of token IDs.

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

Explanation

The reference wraps each prompt in the checkpoint’s chat template before encoding it (generate.py 150). Token IDs index a vocabulary of 129,280 entries; $T$ counts the tokens.

Codegenerate.py 117, 150 · config_671B_v3.2.json 1–26

generate.py 117

    tokenizer = AutoTokenizer.from_pretrained(ckpt_path)

generate.py 150

        prompt_tokens = [tokenizer.apply_chat_template([{"role": "user", "content": prompt}], add_generation_prompt=True) for prompt in prompts]

config_671B_v3.2.json 1–26

{
    "vocab_size": 129280,
    "dim": 7168,
    "inter_dim": 18432,
    "moe_inter_dim": 2048,
    "n_layers": 61,
    "n_dense_layers": 3,
    "n_heads": 128,
    "n_routed_experts": 256,
    "n_shared_experts": 1,
    "n_activated_experts": 8,
    "n_expert_groups": 8,
    "n_limited_groups": 4,
    "route_scale": 2.5,
    "score_func": "sigmoid",
    "q_lora_rank": 1536,
    "kv_lora_rank": 512,
    "qk_nope_head_dim": 128,
    "qk_rope_head_dim": 64,
    "v_head_dim": 128,
    "dtype": "fp8",
    "scale_fmt": "ue8m0",
    "index_n_heads": 64,
    "index_head_dim": 128,
    "index_topk": 2048
}

Sources2

Direct evidence

The reference generator loads the checkpoint’s tokenizer with Hugging Face AutoTokenizer and encodes each prompt through its chat template. The tokenizer’s vocabulary and rules ship with the checkpoint; these sources do not include them.

tokenizer · deepseek-ai/DeepSeek-V3.2-Exp / inference/generate.py
Pinned revision 87e509a2e5a1 ↗ · lines 117–150

Read code excerpt

    tokenizer = AutoTokenizer.from_pretrained(ckpt_path)

… lines 118–149 omitted …

        prompt_tokens = [tokenizer.apply_chat_template([{"role": "user", "content": prompt}], add_generation_prompt=True) for prompt in prompts]

Direct evidence

The released 671B configuration: width, layers, dense layers, heads, experts and routing, MLA ranks and head widths, indexer heads and top-k.

config · deepseek-ai/DeepSeek-V3.2-Exp / inference/config_671B_v3.2.json
Pinned revision 87e509a2e5a1 ↗ · lines 1–26

Read code excerpt

{
    "vocab_size": 129280,
    "dim": 7168,
    "inter_dim": 18432,
    "moe_inter_dim": 2048,
    "n_layers": 61,
    "n_dense_layers": 3,
    "n_heads": 128,
    "n_routed_experts": 256,
    "n_shared_experts": 1,
    "n_activated_experts": 8,
    "n_expert_groups": 8,
    "n_limited_groups": 4,
    "route_scale": 2.5,
    "score_func": "sigmoid",
    "q_lora_rank": 1536,
    "kv_lora_rank": 512,
    "qk_nope_head_dim": 128,
    "qk_rope_head_dim": 64,
    "v_head_dim": 128,
    "dtype": "fp8",
    "scale_fmt": "ue8m0",
    "index_n_heads": 64,
    "index_head_dim": 128,
    "index_topk": 2048
}