srizon/
pixie

Pixie is a combined model powered by dolphin-llama3 and llava who can break complex problems into smaller pieces and find the best solutions using her own pattern. Not only text based, she can read images as well.

vision

3,151 11 months ago

1 Tag
... /
model
170370233dd5 · 4.1GB
    Metadata
  • general.architecture
    llama
  • general.file_type
    Q4_0
  • llama.attention.head_count
    32
  • llama.attention.head_count_kv
    8
  • llama.attention.layer_norm_rms_epsilon
    1e-05
  • llama.block_count
    32
  • llama.context_length
    32768
  • llama.embedding_length
    4096
  • llama.feed_forward_length
    14336
  • llama.rope.dimension_count
    128
  • llama.rope.freq_base
    1e+06
  • tokenizer.ggml.add_bos_token
    true
  • tokenizer.ggml.add_eos_token
    false
  • tokenizer.ggml.bos_token_id
    1
  • tokenizer.ggml.eos_token_id
    2
  • tokenizer.ggml.model
    llama
  • tokenizer.ggml.padding_token_id
    0
  • tokenizer.ggml.scores
    [0, 0, 0, 0, 0, ...]
  • tokenizer.ggml.token_type
    [2, 3, 3, 6, 6, ...]
  • tokenizer.ggml.tokens
    [<unk>, <s>, </s>, <0x00>, <0x01>, ...]
  • tokenizer.ggml.unknown_token_id
    0
    • Tensor
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    F32
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  • blk.26.ffn_up.weight
    Q4_0
    [4096, 14336]
    • blk.27
  • blk.27.attn_k.weight
    Q4_0
    [4096, 1024]
  • blk.27.attn_norm.weight
    F32
    [4096]
  • blk.27.attn_output.weight
    Q4_0
    [4096, 4096]
  • blk.27.attn_q.weight
    Q4_0
    [4096, 4096]
  • blk.27.attn_v.weight
    Q4_0
    [4096, 1024]
  • blk.27.ffn_down.weight
    Q4_0
    [14336, 4096]
  • blk.27.ffn_gate.weight
    Q4_0
    [4096, 14336]
  • blk.27.ffn_norm.weight
    F32
    [4096]
  • blk.27.ffn_up.weight
    Q4_0
    [4096, 14336]
    • blk.28
  • blk.28.attn_k.weight
    Q4_0
    [4096, 1024]
  • blk.28.attn_norm.weight
    F32
    [4096]
  • blk.28.attn_output.weight
    Q4_0
    [4096, 4096]
  • blk.28.attn_q.weight
    Q4_0
    [4096, 4096]
  • blk.28.attn_v.weight
    Q4_0
    [4096, 1024]
  • blk.28.ffn_down.weight
    Q4_0
    [14336, 4096]
  • blk.28.ffn_gate.weight
    Q4_0
    [4096, 14336]
  • blk.28.ffn_norm.weight
    F32
    [4096]
  • blk.28.ffn_up.weight
    Q4_0
    [4096, 14336]
    • blk.29
  • blk.29.attn_k.weight
    Q4_0
    [4096, 1024]
  • blk.29.attn_norm.weight
    F32
    [4096]
  • blk.29.attn_output.weight
    Q4_0
    [4096, 4096]
  • blk.29.attn_q.weight
    Q4_0
    [4096, 4096]
  • blk.29.attn_v.weight
    Q4_0
    [4096, 1024]
  • blk.29.ffn_down.weight
    Q4_0
    [14336, 4096]
  • blk.29.ffn_gate.weight
    Q4_0
    [4096, 14336]
  • blk.29.ffn_norm.weight
    F32
    [4096]
  • blk.29.ffn_up.weight
    Q4_0
    [4096, 14336]
    • blk.30
  • blk.30.attn_k.weight
    Q4_0
    [4096, 1024]
  • blk.30.attn_norm.weight
    F32
    [4096]
  • blk.30.attn_output.weight
    Q4_0
    [4096, 4096]
  • blk.30.attn_q.weight
    Q4_0
    [4096, 4096]
  • blk.30.attn_v.weight
    Q4_0
    [4096, 1024]
  • blk.30.ffn_down.weight
    Q4_0
    [14336, 4096]
  • blk.30.ffn_gate.weight
    Q4_0
    [4096, 14336]
  • blk.30.ffn_norm.weight
    F32
    [4096]
  • blk.30.ffn_up.weight
    Q4_0
    [4096, 14336]
    • blk.31
  • blk.31.attn_k.weight
    Q4_0
    [4096, 1024]
  • blk.31.attn_norm.weight
    F32
    [4096]
  • blk.31.attn_output.weight
    Q4_0
    [4096, 4096]
  • blk.31.attn_q.weight
    Q4_0
    [4096, 4096]
  • blk.31.attn_v.weight
    Q4_0
    [4096, 1024]
  • blk.31.ffn_down.weight
    Q4_0
    [14336, 4096]
  • blk.31.ffn_gate.weight
    Q4_0
    [4096, 14336]
  • blk.31.ffn_norm.weight
    F32
    [4096]
  • blk.31.ffn_up.weight
    Q4_0
    [4096, 14336]
  • output.weight
    Q6_K
    [4096, 32000]
  • output_norm.weight
    F32
    [4096]