A model from NVIDIA based on Llama 3 that excels at conversational question answering (QA) and retrieval-augmented generation (RAG).

8b 70b

81.9K 7 months ago

66eda707426c · 50GB
    Metadata
  • general.architecture
    llama
  • general.file_type
    17
  • general.name
    Llama3-ChatQA-1.5-70B
  • general.quantization_version
    2
  • llama.attention.head_count
    64
  • llama.attention.head_count_kv
    8
  • llama.attention.layer_norm_rms_epsilon
    1e-05
  • llama.block_count
    80
  • llama.context_length
    8192
  • llama.embedding_length
    8192
  • llama.feed_forward_length
    28672
  • llama.rope.dimension_count
    128
  • llama.rope.freq_base
    500000
  • llama.vocab_size
    128256
  • tokenizer.ggml.bos_token_id
    128000
  • tokenizer.ggml.eos_token_id
    128001
  • tokenizer.ggml.merges
    [Ġ Ġ, Ġ ĠĠĠ, ĠĠ ĠĠ, ĠĠĠ Ġ, i n, ...]
  • tokenizer.ggml.model
    gpt2
  • tokenizer.ggml.pre
    llama-bpe
  • tokenizer.ggml.token_type
    [1, 1, 1, 1, 1, ...]
  • tokenizer.ggml.tokens
    [!, ", #, $, %, ...]
  • Tensor
  • Name
    Type
    Shape
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    Q5_K
    [8192, 128256]
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    Q5_K
    [8192, 1024]
  • blk.0.attn_norm.weight
    F32
    [8192]
  • blk.0.attn_output.weight
    Q5_K
    [8192, 8192]
  • blk.0.attn_q.weight
    Q5_K
    [8192, 8192]
  • blk.0.attn_v.weight
    Q6_K
    [8192, 1024]
  • blk.0.ffn_down.weight
    Q6_K
    [28672, 8192]
  • blk.0.ffn_gate.weight
    Q5_K
    [8192, 28672]
  • blk.0.ffn_norm.weight
    F32
    [8192]
  • blk.0.ffn_up.weight
    Q5_K
    [8192, 28672]
  • blk.1
  • blk.1.attn_k.weight
    Q5_K
    [8192, 1024]
  • blk.1.attn_norm.weight
    F32
    [8192]
  • blk.1.attn_output.weight
    Q5_K
    [8192, 8192]
  • blk.1.attn_q.weight
    Q5_K
    [8192, 8192]
  • blk.1.attn_v.weight
    Q6_K
    [8192, 1024]
  • blk.1.ffn_down.weight
    Q6_K
    [28672, 8192]
  • blk.1.ffn_gate.weight
    Q5_K
    [8192, 28672]
  • blk.1.ffn_norm.weight
    F32
    [8192]
  • blk.1.ffn_up.weight
    Q5_K
    [8192, 28672]
  • blk.2
  • blk.2.attn_k.weight
    Q5_K
    [8192, 1024]
  • blk.2.attn_norm.weight
    F32
    [8192]
  • blk.2.attn_output.weight
    Q5_K
    [8192, 8192]
  • blk.2.attn_q.weight
    Q5_K
    [8192, 8192]
  • blk.2.attn_v.weight
    Q6_K
    [8192, 1024]
  • blk.2.ffn_down.weight
    Q6_K
    [28672, 8192]
  • blk.2.ffn_gate.weight
    Q5_K
    [8192, 28672]
  • blk.2.ffn_norm.weight
    F32
    [8192]
  • blk.2.ffn_up.weight
    Q5_K
    [8192, 28672]
  • blk.3
  • blk.3.attn_k.weight
    Q5_K
    [8192, 1024]
  • blk.3.attn_norm.weight
    F32
    [8192]
  • blk.3.attn_output.weight
    Q5_K
    [8192, 8192]
  • blk.3.attn_q.weight
    Q5_K
    [8192, 8192]
  • blk.3.attn_v.weight
    Q6_K
    [8192, 1024]
  • blk.3.ffn_down.weight
    Q6_K
    [28672, 8192]
  • blk.3.ffn_gate.weight
    Q5_K
    [8192, 28672]
  • blk.3.ffn_norm.weight
    F32
    [8192]
  • blk.3.ffn_up.weight
    Q5_K
    [8192, 28672]
  • blk.4
  • blk.4.attn_k.weight
    Q5_K
    [8192, 1024]
  • blk.4.attn_norm.weight
    F32
    [8192]
  • blk.4.attn_output.weight
    Q5_K
    [8192, 8192]
  • blk.4.attn_q.weight
    Q5_K
    [8192, 8192]
  • blk.4.attn_v.weight
    Q6_K
    [8192, 1024]
  • blk.4.ffn_down.weight
    Q6_K
    [28672, 8192]
  • blk.4.ffn_gate.weight
    Q5_K
    [8192, 28672]
  • blk.4.ffn_norm.weight
    F32
    [8192]
  • blk.4.ffn_up.weight
    Q5_K
    [8192, 28672]
  • blk.5
  • blk.5.attn_k.weight
    Q5_K
    [8192, 1024]
  • blk.5.attn_norm.weight
    F32
    [8192]
  • blk.5.attn_output.weight
    Q5_K
    [8192, 8192]
  • blk.5.attn_q.weight
    Q5_K
    [8192, 8192]
  • blk.5.attn_v.weight
    Q6_K
    [8192, 1024]
  • blk.5.ffn_down.weight
    Q6_K
    [28672, 8192]
  • blk.5.ffn_gate.weight
    Q5_K
    [8192, 28672]
  • blk.5.ffn_norm.weight
    F32
    [8192]
  • blk.5.ffn_up.weight
    Q5_K
    [8192, 28672]
  • blk.6
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    Q5_K
    [8192, 1024]
  • blk.6.attn_norm.weight
    F32
    [8192]
  • blk.6.attn_output.weight
    Q5_K
    [8192, 8192]
  • blk.6.attn_q.weight
    Q5_K
    [8192, 8192]
  • blk.6.attn_v.weight
    Q6_K
    [8192, 1024]
  • blk.6.ffn_down.weight
    Q6_K
    [28672, 8192]
  • blk.6.ffn_gate.weight
    Q5_K
    [8192, 28672]
  • blk.6.ffn_norm.weight
    F32
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  • blk.6.ffn_up.weight
    Q5_K
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  • blk.7
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    Q5_K
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  • blk.7.attn_norm.weight
    F32
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  • blk.7.attn_output.weight
    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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    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
    [28672, 8192]
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    Q5_K
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  • blk.8.ffn_norm.weight
    F32
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  • blk.8.ffn_up.weight
    Q5_K
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    Q5_K
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  • blk.9.attn_norm.weight
    F32
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  • blk.9.attn_output.weight
    Q5_K
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  • blk.9.attn_q.weight
    Q5_K
    [8192, 8192]
  • blk.9.attn_v.weight
    Q5_K
    [8192, 1024]
  • blk.9.ffn_down.weight
    Q6_K
    [28672, 8192]
  • blk.9.ffn_gate.weight
    Q5_K
    [8192, 28672]
  • blk.9.ffn_norm.weight
    F32
    [8192]
  • blk.9.ffn_up.weight
    Q5_K
    [8192, 28672]
  • blk.10
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    Q5_K
    [8192, 1024]
  • blk.10.attn_norm.weight
    F32
    [8192]
  • blk.10.attn_output.weight
    Q5_K
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  • blk.10.attn_q.weight
    Q5_K
    [8192, 8192]
  • blk.10.attn_v.weight
    Q6_K
    [8192, 1024]
  • blk.10.ffn_down.weight
    Q5_K
    [28672, 8192]
  • blk.10.ffn_gate.weight
    Q5_K
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  • blk.10.ffn_norm.weight
    F32
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  • blk.10.ffn_up.weight
    Q5_K
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  • blk.11
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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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    Q6_K
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    Q5_K
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  • blk.12.ffn_norm.weight
    F32
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    Q5_K
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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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    Q5_K
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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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    F32
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