Embedding models on very large sentence level datasets.

embedding 22m 33m

171.4K 6 months ago

cb39eaabff82 · 67MB
    Metadata
  • bert.attention.causal
    false
  • bert.attention.head_count
    12
  • bert.attention.layer_norm_epsilon
    1e-12
  • bert.block_count
    12
  • bert.context_length
    512
  • bert.embedding_length
    384
  • bert.feed_forward_length
    1536
  • bert.pooling_type
    1
  • general.architecture
    bert
  • general.file_type
    1
  • general.name
    all-MiniLM-L12-v2
  • tokenizer.ggml.bos_token_id
    101
  • tokenizer.ggml.cls_token_id
    101
  • tokenizer.ggml.eos_token_id
    102
  • tokenizer.ggml.mask_token_id
    103
  • tokenizer.ggml.model
    bert
  • tokenizer.ggml.padding_token_id
    0
  • tokenizer.ggml.scores
    [-1000, -1000, -1000, -1000, -1000, ...]
  • tokenizer.ggml.seperator_token_id
    102
  • tokenizer.ggml.token_type
    [3, 1, 1, 1, 1, ...]
  • tokenizer.ggml.token_type_count
    2
  • tokenizer.ggml.tokens
    [[PAD], [unused0], [unused1], [unused2], [unused3], ...]
  • tokenizer.ggml.unknown_token_id
    100
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