PaliGemma is a versatile and lightweight vision-language model based on open components such as the SigLIP vision model and the Gemma language model.

vision

2,839 2 months ago

ae7696e4f273 · 5.0GB
    Metadata
  • gemma.attention.head_count
    8
  • gemma.attention.head_count_kv
    1
  • gemma.attention.key_length
    256
  • gemma.attention.layer_norm_rms_epsilon
    1e-06
  • gemma.attention.value_length
    256
  • gemma.block_count
    18
  • gemma.context_length
    2048
  • gemma.embedding_length
    2048
  • gemma.feed_forward_length
    16384
  • general.architecture
    gemma
  • general.file_type
    1
  • general.name
    paligemma-3b-mix-224
  • tokenizer.ggml.add_bos_token
    true
  • tokenizer.ggml.add_eos_token
    false
  • tokenizer.ggml.bos_token_id
    2
  • tokenizer.ggml.eos_token_id
    1
  • tokenizer.ggml.model
    llama
  • tokenizer.ggml.padding_token_id
    0
  • tokenizer.ggml.pre
    default
  • tokenizer.ggml.scores
    [0, 0, 0, 0, 0, ...]
  • tokenizer.ggml.token_type
    [3, 3, 3, 2, 1, ...]
  • tokenizer.ggml.tokens
    [<pad>, <eos>, <bos>, <unk>, <mask>, ...]
  • tokenizer.ggml.unknown_token_id
    3
  • Tensor
  • Name
    Type
    Shape
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  • blk.0.attn_norm.weight
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  • blk.0.attn_output.weight
    F16
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  • blk.0.attn_q.weight
    F16
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  • blk.0.attn_v.weight
    F16
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  • blk.0.ffn_down.weight
    F16
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  • blk.0.ffn_gate.weight
    F16
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  • blk.0.ffn_norm.weight
    F32
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  • blk.0.ffn_up.weight
    F16
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  • blk.1
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    F16
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  • blk.1.attn_norm.weight
    F32
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  • blk.1.attn_output.weight
    F16
    [2048, 2048]
  • blk.1.attn_q.weight
    F16
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  • blk.1.attn_v.weight
    F16
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  • blk.1.ffn_down.weight
    F16
    [16384, 2048]
  • blk.1.ffn_gate.weight
    F16
    [2048, 16384]
  • blk.1.ffn_norm.weight
    F32
    [2048]
  • blk.1.ffn_up.weight
    F16
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  • blk.2
  • blk.2.attn_k.weight
    F16
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  • blk.2.attn_norm.weight
    F32
    [2048]
  • blk.2.attn_output.weight
    F16
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  • blk.2.attn_q.weight
    F16
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  • blk.2.attn_v.weight
    F16
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  • blk.2.ffn_down.weight
    F16
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  • blk.2.ffn_gate.weight
    F16
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  • blk.2.ffn_norm.weight
    F32
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  • blk.2.ffn_up.weight
    F16
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    F16
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  • blk.3.attn_norm.weight
    F32
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  • blk.3.attn_output.weight
    F16
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  • blk.3.attn_q.weight
    F16
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  • blk.3.attn_v.weight
    F16
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    F16
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    F16
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    F32
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    F16
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    F16
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    F16
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    F16
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    F16
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    F16
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  • blk.4.ffn_norm.weight
    F32
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    F16
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    F16
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  • blk.5.attn_norm.weight
    F32
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  • blk.5.attn_output.weight
    F16
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  • blk.5.attn_q.weight
    F16
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  • blk.5.attn_v.weight
    F16
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    F16
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    F16
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  • blk.5.ffn_norm.weight
    F32
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    F16
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    F16
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  • blk.6.attn_norm.weight
    F32
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  • blk.6.attn_output.weight
    F16
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  • blk.6.attn_q.weight
    F16
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  • blk.6.attn_v.weight
    F16
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    F16
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    F16
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    F32
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    F16
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    F16
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    F16
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    F16
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    F16
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    F16
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    F16
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    F32
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    F16
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    F16
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    F16
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    F16
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    F16
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    F32
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    F16
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    F32
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    F16
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    F16
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    F16
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    F16
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    F16
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  • blk.10.ffn_norm.weight
    F32
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  • blk.10.ffn_up.weight
    F16
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    F16
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  • blk.11.attn_norm.weight
    F32
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    F16
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    F16
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  • blk.11.attn_v.weight
    F16
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    F16
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    F16
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    F32
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    F16
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    F16
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    F32
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    F16
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    F16
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    F16
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    F16
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    F16
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    F16
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    F16
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  • blk.14.ffn_norm.weight
    F32
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  • blk.14.ffn_up.weight
    F16
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    F16
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  • blk.15.attn_norm.weight
    F32
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  • blk.15.attn_output.weight
    F16
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  • blk.15.attn_q.weight
    F16
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  • blk.15.attn_v.weight
    F16
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    F16
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    F16
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    F32
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    F16
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    F16
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    F16
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    F16
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    F32
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