deepseek-coder:6.7b-instruct-q5_1

967.2K 1 year ago

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

1.3b 6.7b 33b
... /
model
94b697c99a08 · 5.1GB
    Metadata
  • general.architecture
    llama
  • general.file_type
    Q5_1
  • 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
    [!, ", #, $, %, ...]
    • Tensor
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    [4096, 4096]
  • blk.26.ffn_down.weight
    Q5_1
    [11008, 4096]
  • blk.26.ffn_gate.weight
    Q5_1
    [4096, 11008]
  • blk.26.ffn_norm.weight
    F32
    [4096]
  • blk.26.ffn_up.weight
    Q5_1
    [4096, 11008]
    • blk.27
  • blk.27.attn_k.weight
    Q5_1
    [4096, 4096]
  • blk.27.attn_norm.weight
    F32
    [4096]
  • blk.27.attn_output.weight
    Q5_1
    [4096, 4096]
  • blk.27.attn_q.weight
    Q5_1
    [4096, 4096]
  • blk.27.attn_v.weight
    Q5_1
    [4096, 4096]
  • blk.27.ffn_down.weight
    Q5_1
    [11008, 4096]
  • blk.27.ffn_gate.weight
    Q5_1
    [4096, 11008]
  • blk.27.ffn_norm.weight
    F32
    [4096]
  • blk.27.ffn_up.weight
    Q5_1
    [4096, 11008]
    • blk.28
  • blk.28.attn_k.weight
    Q5_1
    [4096, 4096]
  • blk.28.attn_norm.weight
    F32
    [4096]
  • blk.28.attn_output.weight
    Q5_1
    [4096, 4096]
  • blk.28.attn_q.weight
    Q5_1
    [4096, 4096]
  • blk.28.attn_v.weight
    Q5_1
    [4096, 4096]
  • blk.28.ffn_down.weight
    Q5_1
    [11008, 4096]
  • blk.28.ffn_gate.weight
    Q5_1
    [4096, 11008]
  • blk.28.ffn_norm.weight
    F32
    [4096]
  • blk.28.ffn_up.weight
    Q5_1
    [4096, 11008]
    • blk.29
  • blk.29.attn_k.weight
    Q5_1
    [4096, 4096]
  • blk.29.attn_norm.weight
    F32
    [4096]
  • blk.29.attn_output.weight
    Q5_1
    [4096, 4096]
  • blk.29.attn_q.weight
    Q5_1
    [4096, 4096]
  • blk.29.attn_v.weight
    Q5_1
    [4096, 4096]
  • blk.29.ffn_down.weight
    Q5_1
    [11008, 4096]
  • blk.29.ffn_gate.weight
    Q5_1
    [4096, 11008]
  • blk.29.ffn_norm.weight
    F32
    [4096]
  • blk.29.ffn_up.weight
    Q5_1
    [4096, 11008]
    • blk.30
  • blk.30.attn_k.weight
    Q5_1
    [4096, 4096]
  • blk.30.attn_norm.weight
    F32
    [4096]
  • blk.30.attn_output.weight
    Q5_1
    [4096, 4096]
  • blk.30.attn_q.weight
    Q5_1
    [4096, 4096]
  • blk.30.attn_v.weight
    Q5_1
    [4096, 4096]
  • blk.30.ffn_down.weight
    Q5_1
    [11008, 4096]
  • blk.30.ffn_gate.weight
    Q5_1
    [4096, 11008]
  • blk.30.ffn_norm.weight
    F32
    [4096]
  • blk.30.ffn_up.weight
    Q5_1
    [4096, 11008]
    • blk.31
  • blk.31.attn_k.weight
    Q5_1
    [4096, 4096]
  • blk.31.attn_norm.weight
    F32
    [4096]
  • blk.31.attn_output.weight
    Q5_1
    [4096, 4096]
  • blk.31.attn_q.weight
    Q5_1
    [4096, 4096]
  • blk.31.attn_v.weight
    Q5_1
    [4096, 4096]
  • blk.31.ffn_down.weight
    Q5_1
    [11008, 4096]
  • blk.31.ffn_gate.weight
    Q5_1
    [4096, 11008]
  • blk.31.ffn_norm.weight
    F32
    [4096]
  • blk.31.ffn_up.weight
    Q5_1
    [4096, 11008]
  • output.weight
    Q6_K
    [4096, 32256]
  • output_norm.weight
    F32
    [4096]