robit/ kolibri-1:q4_k_m

747 2 weeks ago

Kolibri: A Sovereign European Model on the Pareto Frontier

tools thinking
... /
model
fa6ccc646770 · 65GB
    Metadata
  • general.architecture
    afmoe
  • general.file_type
    Q4_K_M
  • afmoe.attention.head_count
    48
  • afmoe.attention.head_count_kv
    4
  • afmoe.attention.key_length
    128
  • afmoe.attention.layer_norm_rms_epsilon
    1e-06
  • afmoe.attention.sliding_window
    513
  • afmoe.attention.sliding_window_pattern
    [true, true, true, true, true, ...]
  • afmoe.attention.value_length
    128
  • afmoe.block_count
    80
  • afmoe.context_length
    262144
  • afmoe.embedding_length
    2560
  • afmoe.expert_count
    384
  • afmoe.expert_feed_forward_length
    512
  • afmoe.expert_gating_func
    2
  • afmoe.expert_shared_count
    1
  • afmoe.expert_shared_feed_forward_length
    512
  • afmoe.expert_used_count
    6
  • afmoe.expert_weights_norm
    false
  • afmoe.feed_forward_length
    512
  • afmoe.rope.dimension_count
    128
  • afmoe.rope.freq_base
    10000
  • afmoe.rope.scaling.type
    none
  • afmoe.vocab_size
    128000
  • tokenizer.ggml.add_bos_token
    false
  • tokenizer.ggml.add_eos_token
    false
  • tokenizer.ggml.add_space_prefix
    false
  • tokenizer.ggml.eos_token_id
    127906
  • tokenizer.ggml.eot_token_id
    127906
  • tokenizer.ggml.merges
    [t h, c h, i n, in g, â Ģ, ...]
  • tokenizer.ggml.model
    gpt2
  • tokenizer.ggml.padding_token_id
    127901
  • tokenizer.ggml.pre
    qwen2
  • tokenizer.ggml.token_type
    [1, 1, 1, 1, 1, ...]
  • tokenizer.ggml.tokens
    [Ā, ā, Ă, ă, Ą, ...]
  • kolibri.original_layer_mapping
    [0, 1, 2, -1, 3, ...]
  • kolibri.source_repository
    Aleph-Alpha/Kolibri-1-BF16
  • kolibri.source_revision
    7a8f290e7858825c3cf5e4c447ba68345de9f1d3
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  • blk.79.ffn_gate_shexp.weight
    Q4_K
    [2560, 512]
  • blk.79.ffn_norm.weight
    F32
    [2560]
  • blk.79.ffn_up_exps.weight
    Q4_K
    [2560, 512, 384]
  • blk.79.ffn_up_shexp.weight
    Q4_K
    [2560, 512]
  • blk.79.post_attention_norm.weight
    F32
    [2560]
  • blk.79.post_ffw_norm.weight
    F32
    [2560]
  • output.weight
    F32
    [2560, 128000]
  • output_norm.weight
    F32
    [2560]