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

1B 7B 33B

218.3K Pulls Updated 6 months ago

102 Tags

b6dfda3810bc · 7.2GB
  • version
    3
  • parameters
    6.74B
  • Metadata
  • general.architecture
    llama
  • general.file_type
    Q8_0
  • general.name
    deepseek-ai
  • general.quantization_version
    2
  • llama.attention.head_count
    32
  • llama.attention.head_count_kv
    32
  • llama.attention.layer_norm_rms_epsilon
    1e-06
  • llama.block_count
    32
  • llama.context_length
    16384
  • llama.embedding_length
    4096
  • llama.feed_forward_length
    11008
  • 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
    [! " # $ % ...]
  • Tensors
  • Name
    Type
    Shape
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    F32
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    Q8_0
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    F32
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    Q8_0
    [4096 11008]
  • blk.27.ffn_up.weight
    Q8_0
    [4096 11008]
  • blk.27.ffn_norm.weight
    F32
    [4096]
  • blk.27.attn_k.weight
    Q8_0
    [4096 4096]
  • blk.27.attn_output.weight
    Q8_0
    [4096 4096]
  • blk.27.attn_q.weight
    Q8_0
    [4096 4096]
  • blk.27.attn_v.weight
    Q8_0
    [4096 4096]
  • blk.28
  • blk.28.attn_norm.weight
    F32
    [4096]
  • blk.28.ffn_down.weight
    Q8_0
    [11008 4096]
  • blk.28.ffn_gate.weight
    Q8_0
    [4096 11008]
  • blk.28.ffn_up.weight
    Q8_0
    [4096 11008]
  • blk.28.ffn_norm.weight
    F32
    [4096]
  • blk.28.attn_k.weight
    Q8_0
    [4096 4096]
  • blk.28.attn_output.weight
    Q8_0
    [4096 4096]
  • blk.28.attn_q.weight
    Q8_0
    [4096 4096]
  • blk.28.attn_v.weight
    Q8_0
    [4096 4096]
  • blk.29
  • blk.29.attn_norm.weight
    F32
    [4096]
  • blk.29.ffn_down.weight
    Q8_0
    [11008 4096]
  • blk.29.ffn_gate.weight
    Q8_0
    [4096 11008]
  • blk.29.ffn_up.weight
    Q8_0
    [4096 11008]
  • blk.29.ffn_norm.weight
    F32
    [4096]
  • blk.29.attn_k.weight
    Q8_0
    [4096 4096]
  • blk.29.attn_output.weight
    Q8_0
    [4096 4096]
  • blk.29.attn_q.weight
    Q8_0
    [4096 4096]
  • blk.29.attn_v.weight
    Q8_0
    [4096 4096]
  • blk.30
  • blk.30.attn_norm.weight
    F32
    [4096]
  • blk.30.ffn_down.weight
    Q8_0
    [11008 4096]
  • blk.30.ffn_gate.weight
    Q8_0
    [4096 11008]
  • blk.30.ffn_up.weight
    Q8_0
    [4096 11008]
  • blk.30.ffn_norm.weight
    F32
    [4096]
  • blk.30.attn_k.weight
    Q8_0
    [4096 4096]
  • blk.30.attn_output.weight
    Q8_0
    [4096 4096]
  • blk.30.attn_q.weight
    Q8_0
    [4096 4096]
  • blk.30.attn_v.weight
    Q8_0
    [4096 4096]
  • blk.31
  • blk.31.attn_norm.weight
    F32
    [4096]
  • blk.31.ffn_down.weight
    Q8_0
    [11008 4096]
  • blk.31.ffn_gate.weight
    Q8_0
    [4096 11008]
  • blk.31.ffn_up.weight
    Q8_0
    [4096 11008]
  • blk.31.ffn_norm.weight
    F32
    [4096]
  • blk.31.attn_k.weight
    Q8_0
    [4096 4096]
  • blk.31.attn_output.weight
    Q8_0
    [4096 4096]
  • blk.31.attn_q.weight
    Q8_0
    [4096 4096]
  • blk.31.attn_v.weight
    Q8_0
    [4096 4096]