RasxAi Lite adalah sebuah Model Ai yang memiliki ukuran Ringan dan sangat cepat. memiliki pengetahuan luas dalam dunia pemrograman dan teknologi informasi. RasxAi Lite adalah versi yang Ringan dari RasxAi yang memiliki Kecerdasan buatan tingkat tinggi !

1 2 months ago

7462734796d6 · 1.6GB
    Metadata
  • gemma2.attention.head_count
    8
  • gemma2.attention.head_count_kv
    4
  • gemma2.attention.key_length
    256
  • gemma2.attention.layer_norm_rms_epsilon
    1e-06
  • gemma2.attention.sliding_window
    4096
  • gemma2.attention.value_length
    256
  • gemma2.attn_logit_softcapping
    50
  • gemma2.block_count
    26
  • gemma2.context_length
    8192
  • gemma2.embedding_length
    2304
  • gemma2.feed_forward_length
    9216
  • gemma2.final_logit_softcapping
    30
  • general.architecture
    gemma2
  • general.basename
    gemma-2.0
  • general.file_type
    2
  • general.finetune
    it-transformers
  • general.license
    gemma
  • general.name
    Gemma 2.0 2b It Transformers
  • general.quantization_version
    2
  • general.size_label
    2B
  • general.type
    model
  • 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
    [-1000, -1000, -1000, -1000, -1000, ...]
  • 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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    F32
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  • blk.0.attn_output.weight
    Q4_0
    [2048, 2304]
  • blk.0.attn_q.weight
    Q4_0
    [2304, 2048]
  • blk.0.attn_v.weight
    Q4_0
    [2304, 1024]
  • blk.0.ffn_down.weight
    Q4_0
    [9216, 2304]
  • blk.0.ffn_gate.weight
    Q4_0
    [2304, 9216]
  • blk.0.ffn_norm.weight
    F32
    [2304]
  • blk.0.ffn_up.weight
    Q4_0
    [2304, 9216]
  • blk.0.post_attention_norm.weight
    F32
    [2304]
  • blk.0.post_ffw_norm.weight
    F32
    [2304]
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    Q4_0
    [2304, 1024]
  • blk.1.attn_norm.weight
    F32
    [2304]
  • blk.1.attn_output.weight
    Q4_0
    [2048, 2304]
  • blk.1.attn_q.weight
    Q4_0
    [2304, 2048]
  • blk.1.attn_v.weight
    Q4_0
    [2304, 1024]
  • blk.1.ffn_down.weight
    Q4_0
    [9216, 2304]
  • blk.1.ffn_gate.weight
    Q4_0
    [2304, 9216]
  • blk.1.ffn_norm.weight
    F32
    [2304]
  • blk.1.ffn_up.weight
    Q4_0
    [2304, 9216]
  • blk.1.post_attention_norm.weight
    F32
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  • blk.1.post_ffw_norm.weight
    F32
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    Q4_0
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    F32
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    Q4_0
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    Q4_0
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    Q4_0
    [2304, 1024]
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    Q4_0
    [9216, 2304]
  • blk.2.ffn_gate.weight
    Q4_0
    [2304, 9216]
  • blk.2.ffn_norm.weight
    F32
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  • blk.2.ffn_up.weight
    Q4_0
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    F32
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    F32
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    Q4_0
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    Q4_0
    [2304, 9216]
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    F32
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  • blk.3.ffn_up.weight
    Q4_0
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    F32
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    F32
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    Q4_0
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    F32
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    Q4_0
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    Q4_0
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    Q4_0
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    Q4_0
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    Q4_0
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    F32
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    Q4_0
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    F32
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    F32
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    Q4_0
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    F32
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    Q4_0
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    Q4_0
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    Q4_0
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    F32
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    Q4_0
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    F32
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    F32
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    F32
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    Q4_0
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    Q4_0
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    Q4_0
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    Q4_0
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    Q4_0
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    F32
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    Q4_0
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    F32
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    F32
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    Q4_0
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    F32
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    Q4_0
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    Q4_0
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    Q4_0
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    Q4_0
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    Q4_0
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  • blk.8.ffn_norm.weight
    F32
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    Q4_0
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    F32
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    F32
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    Q4_0
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    F32
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    Q4_0
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    Q4_0
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    Q4_0
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    F32
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    F32
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