smollm

🪐 A family of small models with 135M, 360M, and 1.7B parameters, trained on a new high-quality dataset.

135m 360m 1.7b

82.6K 2 months ago

94 Tags
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model
2eafcc7c79ee · 999MB
    Metadata
  • general.architecture
    llama
  • general.basename
    SmolLM
  • general.datasets
    [HuggingFaceTB/smollm-corpus]
  • general.file_type
    14
  • general.languages
    [en]
  • general.license
    apache-2.0
  • general.name
    SmolLM 1.7B
  • general.quantization_version
    2
  • general.size_label
    1.7B
  • general.type
    model
  • llama.attention.head_count
    32
  • llama.attention.head_count_kv
    32
  • llama.attention.layer_norm_rms_epsilon
    1e-05
  • llama.block_count
    24
  • llama.context_length
    2048
  • llama.embedding_length
    2048
  • llama.feed_forward_length
    8192
  • llama.rope.dimension_count
    64
  • llama.rope.freq_base
    10000
  • llama.vocab_size
    49152
  • 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 t, Ġ a, i n, h e, Ġ Ġ, ...]
  • tokenizer.ggml.model
    gpt2
  • tokenizer.ggml.pre
    smollm
  • tokenizer.ggml.token_type
    [3, 3, 3, 3, 3, ...]
  • tokenizer.ggml.tokens
    [<|endoftext|>, <|im_start|>, <|im_end|>, <repo_name>, <reponame>, ...]
  • tokenizer.ggml.unknown_token_id
    0
    • Tensor
  • Name
    Type
    Shape
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    Q6_K
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    Q4_K
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  • blk.0.attn_norm.weight
    F32
    [2048]
  • blk.0.attn_output.weight
    Q4_K
    [2048, 2048]
  • blk.0.attn_q.weight
    Q4_K
    [2048, 2048]
  • blk.0.attn_v.weight
    Q5_K
    [2048, 2048]
  • blk.0.ffn_down.weight
    Q5_K
    [8192, 2048]
  • blk.0.ffn_gate.weight
    Q4_K
    [2048, 8192]
  • blk.0.ffn_norm.weight
    F32
    [2048]
  • blk.0.ffn_up.weight
    Q4_K
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    • blk.1
  • blk.1.attn_k.weight
    Q4_K
    [2048, 2048]
  • blk.1.attn_norm.weight
    F32
    [2048]
  • blk.1.attn_output.weight
    Q4_K
    [2048, 2048]
  • blk.1.attn_q.weight
    Q4_K
    [2048, 2048]
  • blk.1.attn_v.weight
    Q5_K
    [2048, 2048]
  • blk.1.ffn_down.weight
    Q5_K
    [8192, 2048]
  • blk.1.ffn_gate.weight
    Q4_K
    [2048, 8192]
  • blk.1.ffn_norm.weight
    F32
    [2048]
  • blk.1.ffn_up.weight
    Q4_K
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    • blk.2
  • blk.2.attn_k.weight
    Q4_K
    [2048, 2048]
  • blk.2.attn_norm.weight
    F32
    [2048]
  • blk.2.attn_output.weight
    Q4_K
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  • blk.2.attn_q.weight
    Q4_K
    [2048, 2048]
  • blk.2.attn_v.weight
    Q4_K
    [2048, 2048]
  • blk.2.ffn_down.weight
    Q4_K
    [8192, 2048]
  • blk.2.ffn_gate.weight
    Q4_K
    [2048, 8192]
  • blk.2.ffn_norm.weight
    F32
    [2048]
  • blk.2.ffn_up.weight
    Q4_K
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    • blk.3
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    Q4_K
    [2048, 2048]
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    F32
    [2048]
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    Q4_K
    [2048, 2048]
  • blk.3.attn_q.weight
    Q4_K
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  • blk.3.attn_v.weight
    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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    F32
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    Q4_K
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    Q4_K
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  • blk.4.attn_v.weight
    Q4_K
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    Q4_K
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  • blk.4.ffn_gate.weight
    Q4_K
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  • blk.4.ffn_norm.weight
    F32
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  • blk.4.ffn_up.weight
    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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    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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    F32
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    Q4_K
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    Q4_K
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    Q4_K
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    Q4_K
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    Q4_K
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  • blk.6.ffn_norm.weight
    F32
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  • blk.6.ffn_up.weight
    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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    Q4_K
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    Q4_K
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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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    Q4_K
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    Q4_K
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    Q4_K
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    Q4_K
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  • blk.9.ffn_norm.weight
    F32
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  • blk.9.ffn_up.weight
    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.10.attn_v.weight
    Q5_K
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  • blk.10.ffn_down.weight
    Q5_K
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    Q4_K
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  • blk.10.ffn_norm.weight
    F32
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    Q4_K
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    F32
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