nemotron-mini

A commercial-friendly small language model by NVIDIA optimized for roleplay, RAG QA, and function calling.

tools 4b

43.8K 2 months ago

17 Tags
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model
9fe3cb039b72 · 3.1GB
    Metadata
  • general.architecture
    nemotron
  • general.base_model.0.name
    Minitron 4B Base
  • general.base_model.0.organization
    Nvidia
  • general.base_model.0.repo_url
    https://huggingface.co/nvidia/Minitron-4B-Base
  • general.base_model.count
    1
  • general.basename
    Minitron
  • general.file_type
    17
  • general.finetune
    Instruct
  • general.languages
    [en]
  • general.license
    other
  • general.license.link
    https://huggingface.co/nvidia/Nemotron-Mini-4B-Instruct/blob/main/nvidia-community-model-license-aug2024.pdf
  • general.license.name
    nvidia-community-model-license
  • general.name
    Minitron 4B Instruct
  • general.organization
    Nvidia
  • general.quantization_version
    2
  • general.size_label
    4B
  • general.type
    model
  • nemotron.attention.head_count
    24
  • nemotron.attention.head_count_kv
    8
  • nemotron.attention.layer_norm_epsilon
    1e-05
  • nemotron.block_count
    32
  • nemotron.context_length
    4096
  • nemotron.embedding_length
    3072
  • nemotron.feed_forward_length
    9216
  • nemotron.rope.dimension_count
    64
  • nemotron.rope.freq_base
    10000
  • nemotron.rope.scaling.type
    none
  • nemotron.vocab_size
    256000
  • tokenizer.ggml.bos_token_id
    2
  • tokenizer.ggml.eos_token_id
    3
  • tokenizer.ggml.model
    llama
  • tokenizer.ggml.padding_token_id
    0
  • tokenizer.ggml.pre
    default
  • tokenizer.ggml.scores
    [-1000, 0, -1000, -1000, -1000, ...]
  • tokenizer.ggml.token_type
    [3, 2, 3, 3, 4, ...]
  • tokenizer.ggml.tokens
    [<pad>, <unk>, <s>, </s>, <extra_id_0>, ...]
  • tokenizer.ggml.unknown_token_id
    1
    • Tensor
  • Name
    Type
    Shape
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    Q5_K
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    Q5_K
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    F32
    [3072]
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    Q5_K
    [3072, 3072]
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    Q5_K
    [3072, 3072]
  • blk.0.attn_v.weight
    Q6_K
    [3072, 1024]
  • blk.0.ffn_down.weight
    Q6_K
    [9216, 3072]
  • blk.0.ffn_norm.bias
    F32
    [3072]
  • blk.0.ffn_norm.weight
    F32
    [3072]
  • blk.0.ffn_up.weight
    Q5_K
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    Q5_K
    [3072, 1024]
  • blk.1.attn_norm.bias
    F32
    [3072]
  • blk.1.attn_norm.weight
    F32
    [3072]
  • blk.1.attn_output.weight
    Q5_K
    [3072, 3072]
  • blk.1.attn_q.weight
    Q5_K
    [3072, 3072]
  • blk.1.attn_v.weight
    Q6_K
    [3072, 1024]
  • blk.1.ffn_down.weight
    Q6_K
    [9216, 3072]
  • blk.1.ffn_norm.bias
    F32
    [3072]
  • blk.1.ffn_norm.weight
    F32
    [3072]
  • blk.1.ffn_up.weight
    Q5_K
    [3072, 9216]
    • blk.2
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    Q5_K
    [3072, 1024]
  • blk.2.attn_norm.bias
    F32
    [3072]
  • blk.2.attn_norm.weight
    F32
    [3072]
  • blk.2.attn_output.weight
    Q5_K
    [3072, 3072]
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    Q5_K
    [3072, 3072]
  • blk.2.attn_v.weight
    Q6_K
    [3072, 1024]
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    Q6_K
    [9216, 3072]
  • blk.2.ffn_norm.bias
    F32
    [3072]
  • blk.2.ffn_norm.weight
    F32
    [3072]
  • blk.2.ffn_up.weight
    Q5_K
    [3072, 9216]
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    Q5_K
    [3072, 1024]
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    F32
    [3072]
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    F32
    [3072]
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    Q5_K
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    Q5_K
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    Q6_K
    [3072, 1024]
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    Q6_K
    [9216, 3072]
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    F32
    [3072]
  • blk.3.ffn_norm.weight
    F32
    [3072]
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    Q5_K
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    • blk.4
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    Q5_K
    [3072, 1024]
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    F32
    [3072]
  • blk.4.attn_norm.weight
    F32
    [3072]
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    Q5_K
    [3072, 3072]
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    Q5_K
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    Q5_K
    [3072, 1024]
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    Q5_K
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    F32
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    F32
    [3072]
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    Q5_K
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    Q5_K
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    F32
    [3072]
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    F32
    [3072]
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    Q5_K
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    Q5_K
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    Q5_K
    [3072, 1024]
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    Q5_K
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  • blk.5.ffn_norm.bias
    F32
    [3072]
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    F32
    [3072]
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    Q5_K
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    Q5_K
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    F32
    [3072]
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    F32
    [3072]
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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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  • blk.6.ffn_norm.bias
    F32
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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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    Q5_K
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    F32
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    Q5_K
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    F32
    [3072]
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    F32
    [3072]
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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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    F32
    [3072]
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    Q5_K
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    Q5_K
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    F32
    [3072]
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    F32
    [3072]
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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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    F32
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    F32
    [3072]
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    Q5_K
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    Q5_K
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    F32
    [3072]
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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
    [3072, 1024]
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    [3072]
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    [3072]
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    [3072, 3072]
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    [3072, 3072]
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    Q6_K
    [3072, 1024]
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    F32
    [3072]
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    Q5_K
    [3072, 9216]
    • blk.25
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    Q5_K
    [3072, 1024]
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    F32
    [3072]
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    F32
    [3072]
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    Q5_K
    [3072, 3072]
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    Q5_K
    [3072, 3072]
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    Q5_K
    [3072, 1024]
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    Q5_K
    [9216, 3072]
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    F32
    [3072]
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    F32
    [3072]
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    Q5_K
    [3072, 9216]
    • blk.26
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    Q5_K
    [3072, 1024]
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    F32
    [3072]
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    F32
    [3072]
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    [3072, 3072]
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    Q5_K
    [3072, 3072]
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    Q5_K
    [3072, 1024]
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    Q5_K
    [9216, 3072]
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    F32
    [3072]
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    F32
    [3072]
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    Q5_K
    [3072, 9216]
    • blk.27
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    Q5_K
    [3072, 1024]
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    F32
    [3072]
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    [3072]
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    [3072, 3072]
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    [3072, 3072]
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    [3072, 1024]
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    Q6_K
    [9216, 3072]
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    F32
    [3072]
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    F32
    [3072]
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    Q5_K
    [3072, 9216]
    • blk.28
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    Q5_K
    [3072, 1024]
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    F32
    [3072]
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    F32
    [3072]
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    [3072, 3072]
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    Q5_K
    [3072, 3072]
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    [3072, 1024]
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    F32
    [3072]
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    Q5_K
    [3072, 9216]
    • blk.29
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    Q5_K
    [3072, 1024]
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    F32
    [3072]
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    F32
    [3072]
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    Q5_K
    [3072, 3072]
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    Q5_K
    [3072, 3072]
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    Q6_K
    [3072, 1024]
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    Q6_K
    [9216, 3072]
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    F32
    [3072]
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    F32
    [3072]
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    Q5_K
    [3072, 9216]
    • blk.30
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    Q5_K
    [3072, 1024]
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    F32
    [3072]
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    F32
    [3072]
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    [3072, 3072]
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    Q5_K
    [3072, 3072]
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    Q6_K
    [3072, 1024]
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    Q6_K
    [9216, 3072]
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    F32
    [3072]
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    F32
    [3072]
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    Q5_K
    [3072, 9216]
    • blk.31
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    Q5_K
    [3072, 1024]
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    F32
    [3072]
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    F32
    [3072]
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    Q5_K
    [3072, 3072]
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    Q5_K
    [3072, 3072]
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    [3072, 1024]
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    Q6_K
    [9216, 3072]
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    F32
    [3072]
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    F32
    [3072]
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    Q5_K
    [3072, 9216]
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