This model was built using a new Smaug recipe for improving performance on real world multi-turn conversations applied to Meta-Llama-3-70B-Instruct

202 5 months ago

88a2deeccc11 · 40GB
    Metadata
  • general.architecture
    llama
  • general.file_type
    2
  • general.name
    ..
  • 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
  • quantize.imatrix.chunks_count
    200
  • quantize.imatrix.dataset
    /shared/opt/work_models/_imatrix/groups_merged.txt
  • quantize.imatrix.entries_count
    560
  • quantize.imatrix.file
    imatrix.dat
  • 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.padding_token_id
    128001
  • tokenizer.ggml.pre
    smaug-bpe
  • tokenizer.ggml.token_type
    [1, 1, 1, 1, 1, ...]
  • tokenizer.ggml.tokens
    [!, ", #, $, %, ...]
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    Q4_0
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    Q4_0
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    Q4_0
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    Q4_1
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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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    F32
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    Q4_0
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    Q4_0
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    Q4_0
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    Q4_1
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    Q4_0
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  • blk.1.ffn_norm.weight
    F32
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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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    Q4_0
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    Q4_0
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    Q4_1
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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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    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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    Q4_0
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    F32
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