ertghiu256/
Qwen3-4b-tcomanr-merge-v2.5:Q5_K_M

43 1 week ago

This model aims to combine the reasoning, code, and math capabilities of Qwen3 4b 2507 reasoning by merging it with some Qwen3 4b finetunes. This model reasoning is very long.

tools thinking
... /
model
2bcd80d8e53f · 2.9GB
    Metadata
  • general.architecture
    qwen3
  • general.file_type
    Q5_K_M
  • qwen3.attention.head_count
    32
  • qwen3.attention.head_count_kv
    8
  • qwen3.attention.key_length
    128
  • qwen3.attention.layer_norm_rms_epsilon
    1e-06
  • qwen3.attention.value_length
    128
  • qwen3.block_count
    36
  • qwen3.context_length
    262144
  • qwen3.embedding_length
    2560
  • qwen3.feed_forward_length
    9728
  • qwen3.rope.freq_base
    5e+06
  • tokenizer.ggml.add_bos_token
    false
  • tokenizer.ggml.bos_token_id
    151643
  • tokenizer.ggml.eos_token_id
    151645
  • tokenizer.ggml.merges
    [Ġ Ġ, ĠĠ ĠĠ, i n, Ġ t, ĠĠĠĠ ĠĠĠĠ, ...]
  • tokenizer.ggml.model
    gpt2
  • tokenizer.ggml.padding_token_id
    151643
  • tokenizer.ggml.pre
    qwen2
  • tokenizer.ggml.token_type
    [1, 1, 1, 1, 1, ...]
  • tokenizer.ggml.tokens
    [!, ", #, $, %, ...]
    • Tensor
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    Q5_K
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    F32
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    F32
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    Q5_K
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    F32
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    Q5_K
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    Q5_K
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    Q5_K
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    F32
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    Q5_K
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    • blk.24
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    Q5_K
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    F32
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    F32
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    Q5_K
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    F32
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    Q6_K
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    Q6_K
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    Q5_K
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    F32
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    Q5_K
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    • blk.25
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    Q5_K
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    F32
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    F32
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    Q5_K
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    Q5_K
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    F32
    [128]
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    Q5_K
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    Q5_K
    [9728, 2560]
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    Q5_K
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    F32
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    Q5_K
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    • blk.26
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    Q5_K
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    F32
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    F32
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    Q5_K
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    Q5_K
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    F32
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    Q5_K
    [2560, 1024]
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    Q5_K
    [9728, 2560]
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    Q5_K
    [2560, 9728]
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    F32
    [2560]
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    Q5_K
    [2560, 9728]
    • blk.27
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    Q5_K
    [2560, 1024]
  • blk.27.attn_k_norm.weight
    F32
    [128]
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    F32
    [2560]
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    Q5_K
    [4096, 2560]
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    Q5_K
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    F32
    [128]
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    Q6_K
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    Q6_K
    [9728, 2560]
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    Q5_K
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    F32
    [2560]
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    Q5_K
    [2560, 9728]
    • blk.28
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    Q5_K
    [2560, 1024]
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    F32
    [128]
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    F32
    [2560]
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    Q5_K
    [4096, 2560]
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    Q5_K
    [2560, 4096]
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    F32
    [128]
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    Q5_K
    [2560, 1024]
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    Q5_K
    [9728, 2560]
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    Q5_K
    [2560, 9728]
  • blk.28.ffn_norm.weight
    F32
    [2560]
  • blk.28.ffn_up.weight
    Q5_K
    [2560, 9728]
    • blk.29
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    Q5_K
    [2560, 1024]
  • blk.29.attn_k_norm.weight
    F32
    [128]
  • blk.29.attn_norm.weight
    F32
    [2560]
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    Q5_K
    [4096, 2560]
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    Q5_K
    [2560, 4096]
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    F32
    [128]
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    Q5_K
    [2560, 1024]
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    Q5_K
    [9728, 2560]
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    Q5_K
    [2560, 9728]
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    F32
    [2560]
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    Q5_K
    [2560, 9728]
    • blk.30
  • blk.30.attn_k.weight
    Q5_K
    [2560, 1024]
  • blk.30.attn_k_norm.weight
    F32
    [128]
  • blk.30.attn_norm.weight
    F32
    [2560]
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    Q5_K
    [4096, 2560]
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    Q5_K
    [2560, 4096]
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    F32
    [128]
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    Q6_K
    [2560, 1024]
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    Q6_K
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    F32
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    • blk.31
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    Q5_K
    [2560, 1024]
  • blk.31.attn_k_norm.weight
    F32
    [128]
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    F32
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    Q5_K
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    F32
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    Q6_K
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    Q6_K
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    F32
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    • blk.32
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    Q5_K
    [2560, 1024]
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    F32
    [128]
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    F32
    [2560]
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    Q5_K
    [4096, 2560]
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    F32
    [128]
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    Q6_K
    [2560, 1024]
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    Q6_K
    [9728, 2560]
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    F32
    [2560]
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    • blk.33
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    Q5_K
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  • blk.33.attn_k_norm.weight
    F32
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    F32
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    Q5_K
    [4096, 2560]
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    F32
    [128]
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    Q6_K
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    Q6_K
    [9728, 2560]
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    F32
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    • blk.34
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    Q5_K
    [2560, 1024]
  • blk.34.attn_k_norm.weight
    F32
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    F32
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    • blk.35
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    Q5_K
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    F32
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    F32
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