virtuanista/ lfm2.5-8b-a1b-uncensored:q5_k_m

5 2 hours ago

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... /
model
a74eab90412e · 6.0GB
    Metadata
  • general.architecture
    lfm2moe
  • general.file_type
    Q5_K_M
  • lfm2moe.attention.head_count
    32
  • lfm2moe.attention.head_count_kv
    [0, 0, 8, 0, 0, ...]
  • lfm2moe.attention.layer_norm_rms_epsilon
    1e-05
  • lfm2moe.block_count
    24
  • lfm2moe.context_length
    128000
  • lfm2moe.embedding_length
    2048
  • lfm2moe.expert_count
    32
  • lfm2moe.expert_feed_forward_length
    1792
  • lfm2moe.expert_gating_func
    2
  • lfm2moe.expert_used_count
    4
  • lfm2moe.feed_forward_length
    7168
  • lfm2moe.leading_dense_block_count
    2
  • lfm2moe.rope.freq_base
    5e+06
  • lfm2moe.shortconv.l_cache
    3
  • lfm2moe.vocab_size
    128000
  • tokenizer.ggml.bos_token_id
    124894
  • tokenizer.ggml.eos_token_id
    124900
  • tokenizer.ggml.merges
    [ĊĊĊĊĊĊĊĊĊ Ċ, ĊĊĊĊĊĊĊĊ ĊĊ, ĊĊĊĊĊĊĊ ĊĊĊ, ĊĊĊĊĊĊ ĊĊĊĊ, ĊĊĊĊĊ ĊĊĊĊĊ, ...]
  • tokenizer.ggml.model
    gpt2
  • tokenizer.ggml.padding_token_id
    124893
  • tokenizer.ggml.pre
    lfm2
  • tokenizer.ggml.token_type
    [1, 1, 1, 1, 1, ...]
  • tokenizer.ggml.tokens
    [ĊĊĊĊĊĊĊĊĊĊ, ĊĊĊĊĊĊĊĊĊ, ĊĊĊĊĊĊĊĊ, ĊĊĊĊĊĊĊ, ĊĊĊĊĊĊ, ...]
  • quantize.imatrix.chunks_count
    12
  • quantize.imatrix.dataset
    /tmp/calibration.txt
  • quantize.imatrix.entries_count
    154
    • Tensor
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    [2048]
  • blk.21.attn_output.weight
    Q5_K
    [2048, 2048]
  • blk.21.attn_q.weight
    Q5_K
    [2048, 2048]
  • blk.21.attn_q_norm.weight
    F32
    [64]
  • blk.21.attn_v.weight
    Q6_K
    [2048, 512]
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    F32
    [32]
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    Q6_K
    [1792, 2048, 32]
  • blk.21.ffn_gate_exps.weight
    Q5_K
    [2048, 1792, 32]
  • blk.21.ffn_gate_inp.weight
    F32
    [2048, 32]
  • blk.21.ffn_norm.weight
    F32
    [2048]
  • blk.21.ffn_up_exps.weight
    Q5_K
    [2048, 1792, 32]
    • blk.22
  • blk.22.attn_norm.weight
    F32
    [2048]
  • blk.22.exp_probs_b.bias
    F32
    [32]
  • blk.22.ffn_down_exps.weight
    Q6_K
    [1792, 2048, 32]
  • blk.22.ffn_gate_exps.weight
    Q5_K
    [2048, 1792, 32]
  • blk.22.ffn_gate_inp.weight
    F32
    [2048, 32]
  • blk.22.ffn_norm.weight
    F32
    [2048]
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    Q5_K
    [2048, 1792, 32]
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    F32
    [3, 2048]
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    Q5_K
    [2048, 6144]
  • blk.22.shortconv.out_proj.weight
    Q5_K
    [2048, 2048]
    • blk.23
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    F32
    [2048]
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    F32
    [32]
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    Q6_K
    [1792, 2048, 32]
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    Q5_K
    [2048, 1792, 32]
  • blk.23.ffn_gate_inp.weight
    F32
    [2048, 32]
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    F32
    [2048]
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    Q5_K
    [2048, 1792, 32]
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    F32
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    Q5_K
    [2048, 6144]
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    Q5_K
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  • token_embd_norm.weight
    F32
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