deepseek-coder

DeepSeek Coder is a capable coding model trained on two trillion code and natural language tokens.

1.3b 6.7b 33b

374.8K 11 months ago

102 Tags
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model
9d8833106bb7 · 745MB
    Metadata
  • general.architecture
    llama
  • general.file_type
    13
  • general.name
    deepseek-ai
  • general.quantization_version
    2
  • llama.attention.head_count
    16
  • llama.attention.head_count_kv
    16
  • llama.attention.layer_norm_rms_epsilon
    1e-06
  • llama.block_count
    24
  • llama.context_length
    16384
  • llama.embedding_length
    2048
  • llama.feed_forward_length
    5504
  • llama.rope.dimension_count
    128
  • llama.rope.freq_base
    100000
  • llama.rope.scaling.factor
    4
  • llama.rope.scaling.type
    linear
  • tokenizer.ggml.add_bos_token
    true
  • tokenizer.ggml.add_eos_token
    false
  • tokenizer.ggml.bos_token_id
    32013
  • tokenizer.ggml.eos_token_id
    32021
  • tokenizer.ggml.merges
    [Ġ Ġ, Ġ t, Ġ a, i n, h e, ...]
  • tokenizer.ggml.model
    gpt2
  • tokenizer.ggml.padding_token_id
    32014
  • tokenizer.ggml.scores
    [0, 0, 0, 0, 0, ...]
  • tokenizer.ggml.token_type
    [1, 1, 1, 1, 1, ...]
  • tokenizer.ggml.tokens
    [!, ", #, $, %, ...]
    • Tensor
  • Name
    Type
    Shape
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    Q3_K
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    Q3_K
    [2048, 2048]
  • blk.0.attn_norm.weight
    F32
    [2048]
  • blk.0.attn_output.weight
    Q5_K
    [2048, 2048]
  • blk.0.attn_q.weight
    Q3_K
    [2048, 2048]
  • blk.0.attn_v.weight
    Q5_K
    [2048, 2048]
  • blk.0.ffn_down.weight
    Q5_1
    [5504, 2048]
  • blk.0.ffn_gate.weight
    Q3_K
    [2048, 5504]
  • blk.0.ffn_norm.weight
    F32
    [2048]
  • blk.0.ffn_up.weight
    Q3_K
    [2048, 5504]
    • blk.1
  • blk.1.attn_k.weight
    Q3_K
    [2048, 2048]
  • blk.1.attn_norm.weight
    F32
    [2048]
  • blk.1.attn_output.weight
    Q5_K
    [2048, 2048]
  • blk.1.attn_q.weight
    Q3_K
    [2048, 2048]
  • blk.1.attn_v.weight
    Q5_K
    [2048, 2048]
  • blk.1.ffn_down.weight
    Q5_1
    [5504, 2048]
  • blk.1.ffn_gate.weight
    Q3_K
    [2048, 5504]
  • blk.1.ffn_norm.weight
    F32
    [2048]
  • blk.1.ffn_up.weight
    Q3_K
    [2048, 5504]
    • blk.2
  • blk.2.attn_k.weight
    Q3_K
    [2048, 2048]
  • blk.2.attn_norm.weight
    F32
    [2048]
  • blk.2.attn_output.weight
    Q5_K
    [2048, 2048]
  • blk.2.attn_q.weight
    Q3_K
    [2048, 2048]
  • blk.2.attn_v.weight
    Q5_K
    [2048, 2048]
  • blk.2.ffn_down.weight
    Q5_1
    [5504, 2048]
  • blk.2.ffn_gate.weight
    Q3_K
    [2048, 5504]
  • blk.2.ffn_norm.weight
    F32
    [2048]
  • blk.2.ffn_up.weight
    Q3_K
    [2048, 5504]
    • blk.3
  • blk.3.attn_k.weight
    Q3_K
    [2048, 2048]
  • blk.3.attn_norm.weight
    F32
    [2048]
  • blk.3.attn_output.weight
    Q5_K
    [2048, 2048]
  • blk.3.attn_q.weight
    Q3_K
    [2048, 2048]
  • blk.3.attn_v.weight
    Q5_K
    [2048, 2048]
  • blk.3.ffn_down.weight
    Q5_1
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  • blk.3.ffn_gate.weight
    Q3_K
    [2048, 5504]
  • blk.3.ffn_norm.weight
    F32
    [2048]
  • blk.3.ffn_up.weight
    Q3_K
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    • blk.4
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    Q3_K
    [2048, 2048]
  • blk.4.attn_norm.weight
    F32
    [2048]
  • blk.4.attn_output.weight
    Q5_K
    [2048, 2048]
  • blk.4.attn_q.weight
    Q3_K
    [2048, 2048]
  • blk.4.attn_v.weight
    Q5_K
    [2048, 2048]
  • blk.4.ffn_down.weight
    Q5_1
    [5504, 2048]
  • blk.4.ffn_gate.weight
    Q3_K
    [2048, 5504]
  • blk.4.ffn_norm.weight
    F32
    [2048]
  • blk.4.ffn_up.weight
    Q3_K
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    • blk.5
  • blk.5.attn_k.weight
    Q3_K
    [2048, 2048]
  • blk.5.attn_norm.weight
    F32
    [2048]
  • blk.5.attn_output.weight
    Q5_K
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  • blk.5.attn_q.weight
    Q3_K
    [2048, 2048]
  • blk.5.attn_v.weight
    Q5_K
    [2048, 2048]
  • blk.5.ffn_down.weight
    Q5_1
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  • blk.5.ffn_gate.weight
    Q3_K
    [2048, 5504]
  • blk.5.ffn_norm.weight
    F32
    [2048]
  • blk.5.ffn_up.weight
    Q3_K
    [2048, 5504]
    • blk.6
  • blk.6.attn_k.weight
    Q3_K
    [2048, 2048]
  • blk.6.attn_norm.weight
    F32
    [2048]
  • blk.6.attn_output.weight
    Q5_K
    [2048, 2048]
  • blk.6.attn_q.weight
    Q3_K
    [2048, 2048]
  • blk.6.attn_v.weight
    Q5_K
    [2048, 2048]
  • blk.6.ffn_down.weight
    Q5_1
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  • blk.6.ffn_gate.weight
    Q3_K
    [2048, 5504]
  • blk.6.ffn_norm.weight
    F32
    [2048]
  • blk.6.ffn_up.weight
    Q3_K
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    • blk.7
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    Q3_K
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  • blk.7.attn_norm.weight
    F32
    [2048]
  • blk.7.attn_output.weight
    Q5_K
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  • blk.7.attn_q.weight
    Q3_K
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  • blk.7.attn_v.weight
    Q5_K
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  • blk.7.ffn_down.weight
    Q5_1
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    Q3_K
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    F32
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    Q3_K
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    F32
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    Q5_K
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    Q3_K
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  • blk.8.attn_v.weight
    Q5_K
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  • blk.8.ffn_down.weight
    Q5_1
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  • blk.8.ffn_gate.weight
    Q3_K
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  • blk.8.ffn_norm.weight
    F32
    [2048]
  • blk.8.ffn_up.weight
    Q3_K
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    • blk.9
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    Q3_K
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    F32
    [2048]
  • blk.9.attn_output.weight
    Q5_K
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  • blk.9.attn_q.weight
    Q3_K
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  • blk.9.attn_v.weight
    Q5_K
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  • blk.9.ffn_down.weight
    Q5_1
    [5504, 2048]
  • blk.9.ffn_gate.weight
    Q3_K
    [2048, 5504]
  • blk.9.ffn_norm.weight
    F32
    [2048]
  • blk.9.ffn_up.weight
    Q3_K
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    • blk.10
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    Q3_K
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  • blk.10.attn_norm.weight
    F32
    [2048]
  • blk.10.attn_output.weight
    Q5_K
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  • blk.10.attn_q.weight
    Q3_K
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  • blk.10.attn_v.weight
    Q5_K
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  • blk.10.ffn_down.weight
    Q5_1
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  • blk.10.ffn_gate.weight
    Q3_K
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  • blk.10.ffn_norm.weight
    F32
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    Q3_K
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    Q3_K
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    F32
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    Q5_K
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    Q3_K
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    Q5_K
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    Q5_1
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    F32
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    F32
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    Q5_K
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    Q3_K
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    F32
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    Q3_K
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    F32
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    F32
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    Q3_K
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    F32
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    Q5_K
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    Q3_K
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    Q5_K
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    Q5_1
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    F32
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    Q3_K
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    F32
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    Q5_K
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    Q5_K
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    Q5_1
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    Q3_K
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    F32
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  • blk.18.attn_q.weight
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