granite3-moe

The IBM Granite 1B and 3B models are the first mixture of experts (MoE) Granite models from IBM designed for low latency usage.

tools 1b 3b

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model
6bd48eb2b42c · 822MB
    Metadata
  • general.architecture
    granitemoe
  • general.basename
    granite-3.0
  • general.file_type
    15
  • general.finetune
    instruct
  • general.license
    apache-2.0
  • general.name
    Granite 3.0 1b A400M Instruct
  • general.quantization_version
    2
  • general.size_label
    1B-a400M
  • general.tags
    [language, granite-3.0, text-generation]
  • general.type
    model
  • granitemoe.attention.head_count
    16
  • granitemoe.attention.head_count_kv
    8
  • granitemoe.attention.layer_norm_rms_epsilon
    1e-06
  • granitemoe.attention.scale
    0.015625
  • granitemoe.block_count
    24
  • granitemoe.context_length
    4096
  • granitemoe.embedding_length
    1024
  • granitemoe.embedding_scale
    12
  • granitemoe.expert_count
    32
  • granitemoe.expert_used_count
    8
  • granitemoe.feed_forward_length
    512
  • granitemoe.logit_scale
    6
  • granitemoe.residual_scale
    0.22
  • granitemoe.rope.dimension_count
    64
  • granitemoe.rope.freq_base
    10000
  • granitemoe.vocab_size
    49155
  • tokenizer.ggml.add_bos_token
    false
  • tokenizer.ggml.add_space_prefix
    false
  • tokenizer.ggml.bos_token_id
    0
  • tokenizer.ggml.eos_token_id
    0
  • tokenizer.ggml.merges
    [Ġ Ġ, ĠĠ ĠĠ, ĠĠĠĠ ĠĠĠĠ, ĠĠ Ġ, e r, ...]
  • tokenizer.ggml.model
    gpt2
  • tokenizer.ggml.padding_token_id
    0
  • tokenizer.ggml.pre
    refact
  • tokenizer.ggml.token_type
    [3, 3, 3, 3, 3, ...]
  • tokenizer.ggml.tokens
    [<|end_of_text|>, <fim_prefix>, <fim_middle>, <fim_suffix>, <fim_pad>, ...]
    • Tensor
  • Name
    Type
    Shape
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    F32
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  • blk.0.attn_output.weight
    Q4_K
    [1024, 1024]
  • blk.0.attn_q.weight
    Q4_K
    [1024, 1024]
  • blk.0.attn_v.weight
    Q6_K
    [1024, 512]
  • blk.0.ffn_down_exps.weight
    Q6_K
    [512, 1024, 32]
  • blk.0.ffn_gate_exps.weight
    Q4_K
    [1024, 512, 32]
  • blk.0.ffn_gate_inp.weight
    F32
    [1024, 32]
  • blk.0.ffn_norm.weight
    F32
    [1024]
  • blk.0.ffn_up_exps.weight
    Q4_K
    [1024, 512, 32]
    • blk.1
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    Q4_K
    [1024, 512]
  • blk.1.attn_norm.weight
    F32
    [1024]
  • blk.1.attn_output.weight
    Q4_K
    [1024, 1024]
  • blk.1.attn_q.weight
    Q4_K
    [1024, 1024]
  • blk.1.attn_v.weight
    Q6_K
    [1024, 512]
  • blk.1.ffn_down_exps.weight
    Q6_K
    [512, 1024, 32]
  • blk.1.ffn_gate_exps.weight
    Q4_K
    [1024, 512, 32]
  • blk.1.ffn_gate_inp.weight
    F32
    [1024, 32]
  • blk.1.ffn_norm.weight
    F32
    [1024]
  • blk.1.ffn_up_exps.weight
    Q4_K
    [1024, 512, 32]
    • blk.2
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    Q4_K
    [1024, 512]
  • blk.2.attn_norm.weight
    F32
    [1024]
  • blk.2.attn_output.weight
    Q4_K
    [1024, 1024]
  • blk.2.attn_q.weight
    Q4_K
    [1024, 1024]
  • blk.2.attn_v.weight
    Q4_K
    [1024, 512]
  • blk.2.ffn_down_exps.weight
    Q6_K
    [512, 1024, 32]
  • blk.2.ffn_gate_exps.weight
    Q4_K
    [1024, 512, 32]
  • blk.2.ffn_gate_inp.weight
    F32
    [1024, 32]
  • blk.2.ffn_norm.weight
    F32
    [1024]
  • blk.2.ffn_up_exps.weight
    Q4_K
    [1024, 512, 32]
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    Q4_K
    [1024, 512]
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    F32
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    Q4_K
    [1024, 1024]
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    Q4_K
    [1024, 1024]
  • blk.3.attn_v.weight
    Q6_K
    [1024, 512]
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    Q4_K
    [512, 1024, 32]
  • blk.3.ffn_gate_exps.weight
    Q4_K
    [1024, 512, 32]
  • blk.3.ffn_gate_inp.weight
    F32
    [1024, 32]
  • blk.3.ffn_norm.weight
    F32
    [1024]
  • blk.3.ffn_up_exps.weight
    Q4_K
    [1024, 512, 32]
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    Q4_K
    [1024, 512]
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    F32
    [1024]
  • blk.4.attn_output.weight
    Q4_K
    [1024, 1024]
  • blk.4.attn_q.weight
    Q4_K
    [1024, 1024]
  • blk.4.attn_v.weight
    Q4_K
    [1024, 512]
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    Q4_K
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  • blk.4.ffn_gate_exps.weight
    Q4_K
    [1024, 512, 32]
  • blk.4.ffn_gate_inp.weight
    F32
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    F32
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    Q4_K
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    Q4_K
    [1024, 512]
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    F32
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    Q4_K
    [1024, 1024]
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    Q4_K
    [1024, 1024]
  • blk.5.attn_v.weight
    Q4_K
    [1024, 512]
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    Q6_K
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  • blk.5.ffn_gate_exps.weight
    Q4_K
    [1024, 512, 32]
  • blk.5.ffn_gate_inp.weight
    F32
    [1024, 32]
  • blk.5.ffn_norm.weight
    F32
    [1024]
  • blk.5.ffn_up_exps.weight
    Q4_K
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    • blk.6
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    Q4_K
    [1024, 512]
  • blk.6.attn_norm.weight
    F32
    [1024]
  • blk.6.attn_output.weight
    Q4_K
    [1024, 1024]
  • blk.6.attn_q.weight
    Q4_K
    [1024, 1024]
  • blk.6.attn_v.weight
    Q6_K
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    Q4_K
    [512, 1024, 32]
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    Q4_K
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  • blk.6.ffn_gate_inp.weight
    F32
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    F32
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    Q4_K
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    Q4_K
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    Q6_K
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    Q4_K
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    Q4_K
    [1024, 512, 32]
  • blk.7.ffn_gate_inp.weight
    F32
    [1024, 32]
  • blk.7.ffn_norm.weight
    F32
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    Q4_K
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    F32
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    Q4_K
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    Q4_K
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    Q6_K
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    Q6_K
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    Q4_K
    [1024, 512, 32]
  • blk.8.ffn_gate_inp.weight
    F32
    [1024, 32]
  • blk.8.ffn_norm.weight
    F32
    [1024]
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    Q4_K
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    Q4_K
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    F32
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    Q4_K
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    Q4_K
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  • blk.9.attn_v.weight
    Q6_K
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    Q4_K
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  • blk.9.ffn_gate_exps.weight
    Q4_K
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  • blk.9.ffn_gate_inp.weight
    F32
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  • blk.9.ffn_norm.weight
    F32
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    Q4_K
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    F32
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    Q4_K
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    Q4_K
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    Q4_K
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    F32
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    Q4_K
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    Q4_K
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    Q4_K
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    F32
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    Q4_K
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    F32
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    F32
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    F32
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    Q4_K
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  • blk.13.ffn_gate_inp.weight
    F32
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  • blk.13.ffn_norm.weight
    F32
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    [1024]
  • blk.23.attn_output.weight
    Q4_K
    [1024, 1024]
  • blk.23.attn_q.weight
    Q4_K
    [1024, 1024]
  • blk.23.attn_v.weight
    Q4_K
    [1024, 512]
  • blk.23.ffn_down_exps.weight
    Q6_K
    [512, 1024, 32]
  • blk.23.ffn_gate_exps.weight
    Q4_K
    [1024, 512, 32]
  • blk.23.ffn_gate_inp.weight
    F32
    [1024, 32]
  • blk.23.ffn_norm.weight
    F32
    [1024]
  • blk.23.ffn_up_exps.weight
    Q4_K
    [1024, 512, 32]
  • output_norm.weight
    F32
    [1024]