exaone-deep:2.4b

149.6K 5 months ago

EXAONE Deep exhibits superior capabilities in various reasoning tasks including math and coding benchmarks, ranging from 2.4B to 32B parameters developed and released by LG AI Research.

2.4b 7.8b 32b
... /
model
1eefef7fedff · 1.6GB
    Metadata
  • general.architecture
    exaone
  • general.file_type
    Q4_K_M
  • exaone.attention.head_count
    32
  • exaone.attention.head_count_kv
    8
  • exaone.attention.layer_norm_rms_epsilon
    1e-05
  • exaone.block_count
    30
  • exaone.context_length
    32768
  • exaone.embedding_length
    2560
  • exaone.feed_forward_length
    7168
  • exaone.rope.dimension_count
    80
  • exaone.rope.freq_base
    1e+06
  • tokenizer.ggml.bos_token_id
    1
  • tokenizer.ggml.eos_token_id
    361
  • tokenizer.ggml.merges
    [t h, Ġ a, Ġ í, i n, Ġ th, ...]
  • tokenizer.ggml.model
    gpt2
  • tokenizer.ggml.padding_token_id
    0
  • tokenizer.ggml.pre
    exaone
  • tokenizer.ggml.token_type
    [3, 3, 3, 3, 4, ...]
  • tokenizer.ggml.tokens
    [[PAD], [BOS], [EOS], [UNK], , ...]
  • tokenizer.ggml.unknown_token_id
    3
    • Tensor
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  • blk.26.ffn_up.weight
    Q4_K
    [2560, 7168]
    • blk.27
  • blk.27.attn_k.weight
    Q4_K
    [2560, 640]
  • blk.27.attn_norm.weight
    F32
    [2560]
  • blk.27.attn_output.weight
    Q4_K
    [2560, 2560]
  • blk.27.attn_q.weight
    Q4_K
    [2560, 2560]
  • blk.27.attn_v.weight
    Q6_K
    [2560, 640]
  • blk.27.ffn_down.weight
    Q6_K
    [7168, 2560]
  • blk.27.ffn_gate.weight
    Q4_K
    [2560, 7168]
  • blk.27.ffn_norm.weight
    F32
    [2560]
  • blk.27.ffn_up.weight
    Q4_K
    [2560, 7168]
    • blk.28
  • blk.28.attn_k.weight
    Q4_K
    [2560, 640]
  • blk.28.attn_norm.weight
    F32
    [2560]
  • blk.28.attn_output.weight
    Q4_K
    [2560, 2560]
  • blk.28.attn_q.weight
    Q4_K
    [2560, 2560]
  • blk.28.attn_v.weight
    Q6_K
    [2560, 640]
  • blk.28.ffn_down.weight
    Q6_K
    [7168, 2560]
  • blk.28.ffn_gate.weight
    Q4_K
    [2560, 7168]
  • blk.28.ffn_norm.weight
    F32
    [2560]
  • blk.28.ffn_up.weight
    Q4_K
    [2560, 7168]
    • blk.29
  • blk.29.attn_k.weight
    Q4_K
    [2560, 640]
  • blk.29.attn_norm.weight
    F32
    [2560]
  • blk.29.attn_output.weight
    Q4_K
    [2560, 2560]
  • blk.29.attn_q.weight
    Q4_K
    [2560, 2560]
  • blk.29.attn_v.weight
    Q6_K
    [2560, 640]
  • blk.29.ffn_down.weight
    Q6_K
    [7168, 2560]
  • blk.29.ffn_gate.weight
    Q4_K
    [2560, 7168]
  • blk.29.ffn_norm.weight
    F32
    [2560]
  • blk.29.ffn_up.weight
    Q4_K
    [2560, 7168]
  • output.weight
    Q6_K
    [2560, 102400]
  • rope_freqs.weight
    F32
    [40]
  • output_norm.weight
    F32
    [2560]