gemma2

Google Gemma 2 is a high-performing and efficient model available in three sizes: 2B, 9B, and 27B.

2b 9b 27b

2M 3 months ago

94 Tags
... /
model
925208c9e9fc · 19GB
    Metadata
  • gemma2.attention.head_count
    32
  • gemma2.attention.head_count_kv
    16
  • gemma2.attention.key_length
    128
  • gemma2.attention.layer_norm_rms_epsilon
    1e-06
  • gemma2.attention.sliding_window
    4096
  • gemma2.attention.value_length
    128
  • gemma2.attn_logit_softcapping
    50
  • gemma2.block_count
    46
  • gemma2.context_length
    8192
  • gemma2.embedding_length
    4608
  • gemma2.feed_forward_length
    36864
  • gemma2.final_logit_softcapping
    30
  • general.architecture
    gemma2
  • general.file_type
    17
  • general.name
    gemma-2-27b
  • general.quantization_version
    2
  • tokenizer.ggml.add_bos_token
    true
  • tokenizer.ggml.add_eos_token
    false
  • tokenizer.ggml.add_space_prefix
    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, 3, 3, ...]
  • tokenizer.ggml.tokens
    [<pad>, <eos>, <bos>, <unk>, <mask>, ...]
  • tokenizer.ggml.unknown_token_id
    3
    • Tensor
  • Name
    Type
    Shape
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    Q6_K
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    Q5_K
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  • blk.0.attn_norm.weight
    F32
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    Q5_K
    [4096, 4608]
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    Q5_K
    [4608, 4096]
  • blk.0.attn_v.weight
    Q6_K
    [4608, 2048]
  • blk.0.ffn_down.weight
    Q6_K
    [36864, 4608]
  • blk.0.ffn_gate.weight
    Q5_K
    [4608, 36864]
  • blk.0.ffn_norm.weight
    F32
    [4608]
  • blk.0.ffn_up.weight
    Q5_K
    [4608, 36864]
  • blk.0.post_attention_norm.weight
    F32
    [4608]
  • blk.0.post_ffw_norm.weight
    F32
    [4608]
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    Q5_K
    [4608, 2048]
  • blk.1.attn_norm.weight
    F32
    [4608]
  • blk.1.attn_output.weight
    Q5_K
    [4096, 4608]
  • blk.1.attn_q.weight
    Q5_K
    [4608, 4096]
  • blk.1.attn_v.weight
    Q6_K
    [4608, 2048]
  • blk.1.ffn_down.weight
    Q6_K
    [36864, 4608]
  • blk.1.ffn_gate.weight
    Q5_K
    [4608, 36864]
  • blk.1.ffn_norm.weight
    F32
    [4608]
  • blk.1.ffn_up.weight
    Q5_K
    [4608, 36864]
  • blk.1.post_attention_norm.weight
    F32
    [4608]
  • blk.1.post_ffw_norm.weight
    F32
    [4608]
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    Q5_K
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    F32
    [4608]
  • blk.2.attn_output.weight
    Q5_K
    [4096, 4608]
  • blk.2.attn_q.weight
    Q5_K
    [4608, 4096]
  • blk.2.attn_v.weight
    Q6_K
    [4608, 2048]
  • blk.2.ffn_down.weight
    Q6_K
    [36864, 4608]
  • blk.2.ffn_gate.weight
    Q5_K
    [4608, 36864]
  • blk.2.ffn_norm.weight
    F32
    [4608]
  • blk.2.ffn_up.weight
    Q5_K
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    F32
    [4608]
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    Q6_K
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    Q5_K
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    F32
    [4608]
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    Q5_K
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    F32
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    F32
    [4608]
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    Q5_K
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    F32
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    Q5_K
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    Q5_K
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    Q6_K
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    Q6_K
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    Q5_K
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    F32
    [4608]
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    Q5_K
    [4608, 36864]
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    F32
    [4608]
  • blk.4.post_ffw_norm.weight
    F32
    [4608]
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    Q5_K
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    F32
    [4608]
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    Q5_K
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    Q5_K
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    Q5_K
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    Q5_K
    [36864, 4608]
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    Q5_K
    [4608, 36864]
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    F32
    [4608]
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    Q5_K
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    F32
    [4608]
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    F32
    [4608]
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    Q5_K
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    Q5_K
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    F32
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    Q5_K
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    Q5_K
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    Q6_K
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    Q6_K
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    Q5_K
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    F32
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    Q5_K
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    F32
    [4608]
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    F32
    [4608]
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    Q5_K
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    F32
    [4608]
  • blk.8.attn_output.weight
    Q5_K
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    Q5_K
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  • blk.8.attn_v.weight
    Q5_K
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    Q5_K
    [36864, 4608]
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    Q5_K
    [4608, 36864]
  • blk.8.ffn_norm.weight
    F32
    [4608]
  • blk.8.ffn_up.weight
    Q5_K
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  • blk.8.post_attention_norm.weight
    F32
    [4608]
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    F32
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    Q5_K
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    F32
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    Q5_K
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    Q5_K
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    Q6_K
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    Q5_K
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    Q5_K
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    F32
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    Q6_K
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    F32
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    F32
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    F32
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    Q5_K
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    F32
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    Q5_K
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    Q5_K
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    Q5_K
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    F32
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  • blk.45.ffn_up.weight
    Q5_K
    [4608, 36864]
  • blk.45.post_attention_norm.weight
    F32
    [4608]
  • blk.45.post_ffw_norm.weight
    F32
    [4608]
  • output_norm.weight
    F32
    [4608]