olmo2

OLMo 2 is a new family of 7B and 13B models trained on up to 5T tokens. These models are on par with or better than equivalently sized fully open models, and competitive with open-weight models such as Llama 3.1 on English academic benchmarks.

7b 13b

4,329 6 days ago

9 Tags
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model
ea89e3927d5e · 4.5GB
    Metadata
  • general.architecture
    olmo2
  • general.base_model.0.name
    OLMo 2 1124 7B DPO
  • general.base_model.0.organization
    Allenai
  • general.base_model.0.repo_url
    https://huggingface.co/allenai/OLMo-2-1124-7B-DPO
  • general.base_model.count
    1
  • general.basename
    OLMo-2-1124
  • general.dataset.0.name
    RLVR GSM
  • general.dataset.0.organization
    Allenai
  • general.dataset.0.repo_url
    https://huggingface.co/allenai/RLVR-GSM
  • general.dataset.count
    1
  • general.file_type
    15
  • general.finetune
    Instruct
  • general.languages
    [en]
  • general.license
    apache-2.0
  • general.name
    Open_Instruct_Dev
  • general.organization
    Allenai
  • general.quantization_version
    2
  • general.size_label
    7B
  • general.tags
    [text-generation]
  • general.type
    model
  • olmo2.attention.head_count
    32
  • olmo2.attention.head_count_kv
    32
  • olmo2.attention.layer_norm_rms_epsilon
    1e-06
  • olmo2.block_count
    32
  • olmo2.context_length
    4096
  • olmo2.embedding_length
    4096
  • olmo2.feed_forward_length
    11008
  • olmo2.rope.freq_base
    500000
  • tokenizer.ggml.bos_token_id
    100257
  • tokenizer.ggml.eos_token_id
    100257
  • tokenizer.ggml.merges
    [Ġ Ġ, ĠĠ ĠĠ, i n, Ġ t, ĠĠĠĠ ĠĠĠĠ, ...]
  • tokenizer.ggml.model
    gpt2
  • tokenizer.ggml.padding_token_id
    100277
  • tokenizer.ggml.pre
    dbrx
  • tokenizer.ggml.token_type
    [1, 1, 1, 1, 1, ...]
  • tokenizer.ggml.tokens
    [!, ", #, $, %, ...]
  • tokenizer.ggml.unknown_token_id
    100257
    • Tensor
  • Name
    Type
    Shape
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    Q4_K
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    Q4_K
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    Q4_K
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  • blk.0.attn_q_norm.weight
    F32
    [4096]
  • blk.0.attn_v.weight
    Q6_K
    [4096, 4096]
  • blk.0.ffn_down.weight
    Q6_K
    [11008, 4096]
  • blk.0.ffn_gate.weight
    Q4_K
    [4096, 11008]
  • blk.0.ffn_up.weight
    Q4_K
    [4096, 11008]
  • blk.0.post_attention_norm.weight
    F32
    [4096]
  • blk.0.post_ffw_norm.weight
    F32
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    Q4_K
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    F32
    [4096]
  • blk.1.attn_output.weight
    Q4_K
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    Q4_K
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  • blk.1.attn_q_norm.weight
    F32
    [4096]
  • blk.1.attn_v.weight
    Q6_K
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  • blk.1.ffn_down.weight
    Q6_K
    [11008, 4096]
  • blk.1.ffn_gate.weight
    Q4_K
    [4096, 11008]
  • blk.1.ffn_up.weight
    Q4_K
    [4096, 11008]
  • blk.1.post_attention_norm.weight
    F32
    [4096]
  • blk.1.post_ffw_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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  • blk.2.attn_q_norm.weight
    F32
    [4096]
  • blk.2.attn_v.weight
    Q6_K
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    Q6_K
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    Q4_K
    [4096, 11008]
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    Q4_K
    [4096, 11008]
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    F32
    [4096]
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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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  • blk.3.attn_q_norm.weight
    F32
    [4096]
  • blk.3.attn_v.weight
    Q6_K
    [4096, 4096]
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    Q6_K
    [11008, 4096]
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    Q4_K
    [4096, 11008]
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    Q4_K
    [4096, 11008]
  • blk.3.post_attention_norm.weight
    F32
    [4096]
  • blk.3.post_ffw_norm.weight
    F32
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    Q4_K
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    F32
    [4096]
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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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    F32
    [4096]
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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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    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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    F32
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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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    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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    F32
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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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    Q4_K
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    Q4_K
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    Q4_K
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    F32
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    F32
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