smollm

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

135m 360m 1.7b

96.8K 3 months ago

94 Tags
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model
376631d6eb80 · 110MB
    Metadata
  • general.architecture
    llama
  • general.base_model.0.name
    SmolLM 135M
  • general.base_model.0.organization
    HuggingFaceTB
  • general.base_model.0.repo_url
    https://huggingface.co/HuggingFaceTB/SmolLM-135M
  • general.base_model.count
    1
  • general.basename
    SmolLM
  • general.datasets
    [Magpie-Align/Magpie-Pro-300K-Filtered, bigcode/self-oss-instruct-sc2-exec-filter-50k, teknium/OpenHermes-2.5, HuggingFaceTB/everyday-conversations-llama3.1-2k]
  • general.file_type
    16
  • general.finetune
    Instruct
  • general.languages
    [en]
  • general.license
    apache-2.0
  • general.name
    SmolLM 135M
  • general.organization
    HuggingFaceTB
  • general.quantization_version
    2
  • general.size_label
    135M
  • general.tags
    [alignment-handbook, trl, sft]
  • general.type
    model
  • llama.attention.head_count
    9
  • llama.attention.head_count_kv
    3
  • llama.attention.layer_norm_rms_epsilon
    1e-05
  • llama.block_count
    30
  • llama.context_length
    2048
  • llama.embedding_length
    576
  • llama.feed_forward_length
    1536
  • 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
    1
  • tokenizer.ggml.eos_token_id
    2
  • tokenizer.ggml.merges
    [Ġ t, Ġ a, i n, h e, Ġ Ġ, ...]
  • tokenizer.ggml.model
    gpt2
  • tokenizer.ggml.padding_token_id
    2
  • 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
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    Type
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    Q5_K
    [1536, 576]
  • blk.26.ffn_gate.weight
    Q5_1
    [576, 1536]
  • blk.26.ffn_norm.weight
    F32
    [576]
  • blk.26.ffn_up.weight
    Q5_1
    [576, 1536]
    • blk.27
  • blk.27.attn_k.weight
    Q5_1
    [576, 192]
  • blk.27.attn_norm.weight
    F32
    [576]
  • blk.27.attn_output.weight
    Q5_1
    [576, 576]
  • blk.27.attn_q.weight
    Q5_1
    [576, 576]
  • blk.27.attn_v.weight
    Q5_1
    [576, 192]
  • blk.27.ffn_down.weight
    Q5_K
    [1536, 576]
  • blk.27.ffn_gate.weight
    Q5_1
    [576, 1536]
  • blk.27.ffn_norm.weight
    F32
    [576]
  • blk.27.ffn_up.weight
    Q5_1
    [576, 1536]
    • blk.28
  • blk.28.attn_k.weight
    Q5_1
    [576, 192]
  • blk.28.attn_norm.weight
    F32
    [576]
  • blk.28.attn_output.weight
    Q5_1
    [576, 576]
  • blk.28.attn_q.weight
    Q5_1
    [576, 576]
  • blk.28.attn_v.weight
    Q5_1
    [576, 192]
  • blk.28.ffn_down.weight
    Q5_K
    [1536, 576]
  • blk.28.ffn_gate.weight
    Q5_1
    [576, 1536]
  • blk.28.ffn_norm.weight
    F32
    [576]
  • blk.28.ffn_up.weight
    Q5_1
    [576, 1536]
    • blk.29
  • blk.29.attn_k.weight
    Q5_1
    [576, 192]
  • blk.29.attn_norm.weight
    F32
    [576]
  • blk.29.attn_output.weight
    Q5_1
    [576, 576]
  • blk.29.attn_q.weight
    Q5_1
    [576, 576]
  • blk.29.attn_v.weight
    Q5_1
    [576, 192]
  • blk.29.ffn_down.weight
    Q5_K
    [1536, 576]
  • blk.29.ffn_gate.weight
    Q5_1
    [576, 1536]
  • blk.29.ffn_norm.weight
    F32
    [576]
  • blk.29.ffn_up.weight
    Q5_1
    [576, 1536]
  • output_norm.weight
    F32
    [576]