ANVEAI/
anveai-ceo-model:latest

34 4 months ago

The ANVE.AI CEO Agent is a domain-specialized language model finetuned from Qwen3, tailored for CEOs and senior executives. It’s designed to handle strategic leadership tasks like planning, investor communication, and simulating virtual agents.

... /
model
4c7aac58a6cf · 3.4GB
    Metadata
  • general.architecture
    qwen3
  • general.file_type
    F16
  • qwen3.attention.head_count
    16
  • qwen3.attention.head_count_kv
    8
  • qwen3.attention.key_length
    128
  • qwen3.attention.layer_norm_rms_epsilon
    1e-06
  • qwen3.attention.value_length
    128
  • qwen3.block_count
    28
  • qwen3.context_length
    40960
  • qwen3.embedding_length
    2048
  • qwen3.feed_forward_length
    6144
  • qwen3.rope.freq_base
    1e+06
  • tokenizer.ggml.add_bos_token
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  • tokenizer.ggml.bos_token_id
    151643
  • tokenizer.ggml.eos_token_id
    151645
  • tokenizer.ggml.merges
    [Ġ Ġ, ĠĠ ĠĠ, i n, Ġ t, ĠĠĠĠ ĠĠĠĠ, ...]
  • tokenizer.ggml.model
    gpt2
  • tokenizer.ggml.padding_token_id
    151643
  • tokenizer.ggml.pre
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  • tokenizer.ggml.token_type
    [1, 1, 1, 1, 1, ...]
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    [!, ", #, $, %, ...]
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    [2048, 2048]
  • blk.23.attn_q.weight
    F16
    [2048, 2048]
  • blk.23.attn_q_norm.weight
    F32
    [128]
  • blk.23.attn_v.weight
    F16
    [2048, 1024]
  • blk.23.ffn_down.weight
    F16
    [6144, 2048]
  • blk.23.ffn_gate.weight
    F16
    [2048, 6144]
  • blk.23.ffn_norm.weight
    F32
    [2048]
  • blk.23.ffn_up.weight
    F16
    [2048, 6144]
    • blk.24
  • blk.24.attn_k.weight
    F16
    [2048, 1024]
  • blk.24.attn_k_norm.weight
    F32
    [128]
  • blk.24.attn_norm.weight
    F32
    [2048]
  • blk.24.attn_output.weight
    F16
    [2048, 2048]
  • blk.24.attn_q.weight
    F16
    [2048, 2048]
  • blk.24.attn_q_norm.weight
    F32
    [128]
  • blk.24.attn_v.weight
    F16
    [2048, 1024]
  • blk.24.ffn_down.weight
    F16
    [6144, 2048]
  • blk.24.ffn_gate.weight
    F16
    [2048, 6144]
  • blk.24.ffn_norm.weight
    F32
    [2048]
  • blk.24.ffn_up.weight
    F16
    [2048, 6144]
    • blk.25
  • blk.25.attn_k.weight
    F16
    [2048, 1024]
  • blk.25.attn_k_norm.weight
    F32
    [128]
  • blk.25.attn_norm.weight
    F32
    [2048]
  • blk.25.attn_output.weight
    F16
    [2048, 2048]
  • blk.25.attn_q.weight
    F16
    [2048, 2048]
  • blk.25.attn_q_norm.weight
    F32
    [128]
  • blk.25.attn_v.weight
    F16
    [2048, 1024]
  • blk.25.ffn_down.weight
    F16
    [6144, 2048]
  • blk.25.ffn_gate.weight
    F16
    [2048, 6144]
  • blk.25.ffn_norm.weight
    F32
    [2048]
  • blk.25.ffn_up.weight
    F16
    [2048, 6144]
    • blk.26
  • blk.26.attn_k.weight
    F16
    [2048, 1024]
  • blk.26.attn_k_norm.weight
    F32
    [128]
  • blk.26.attn_norm.weight
    F32
    [2048]
  • blk.26.attn_output.weight
    F16
    [2048, 2048]
  • blk.26.attn_q.weight
    F16
    [2048, 2048]
  • blk.26.attn_q_norm.weight
    F32
    [128]
  • blk.26.attn_v.weight
    F16
    [2048, 1024]
  • blk.26.ffn_down.weight
    F16
    [6144, 2048]
  • blk.26.ffn_gate.weight
    F16
    [2048, 6144]
  • blk.26.ffn_norm.weight
    F32
    [2048]
  • blk.26.ffn_up.weight
    F16
    [2048, 6144]
    • blk.27
  • blk.27.attn_k.weight
    F16
    [2048, 1024]
  • blk.27.attn_k_norm.weight
    F32
    [128]
  • blk.27.attn_norm.weight
    F32
    [2048]
  • blk.27.attn_output.weight
    F16
    [2048, 2048]
  • blk.27.attn_q.weight
    F16
    [2048, 2048]
  • blk.27.attn_q_norm.weight
    F32
    [128]
  • blk.27.attn_v.weight
    F16
    [2048, 1024]
  • blk.27.ffn_down.weight
    F16
    [6144, 2048]
  • blk.27.ffn_gate.weight
    F16
    [2048, 6144]
  • blk.27.ffn_norm.weight
    F32
    [2048]
  • blk.27.ffn_up.weight
    F16
    [2048, 6144]
  • output_norm.weight
    F32
    [2048]