Experimental model for generating stories with only 656K parameters!

41 Pulls Updated 2 months ago

e06e68395e91 · 749kB
    Metadata
  • general.architecture
    llama
  • general.file_type
    Q8_0
  • general.quantization_version
    2
  • llama.attention.head_count
    8
  • llama.attention.head_count_kv
    4
  • llama.attention.layer_norm_rms_epsilon
    1e-06
  • llama.block_count
    2
  • llama.context_length
    512
  • llama.embedding_length
    128
  • llama.feed_forward_length
    384
  • llama.rope.dimension_count
    16
  • llama.rope.freq_base
    10000
  • llama.vocab_size
    2048
  • tokenizer.ggml.add_bos_token
    true
  • tokenizer.ggml.add_eos_token
    false
  • tokenizer.ggml.bos_token_id
    1
  • tokenizer.ggml.eos_token_id
    2
  • tokenizer.ggml.model
    llama
  • tokenizer.ggml.padding_token_id
    0
  • tokenizer.ggml.pre
    default
  • tokenizer.ggml.scores
    [-1000 -1000 -1000 -1000 -1000 ...]
  • tokenizer.ggml.token_type
    [3 3 3 1 1 ...]
  • tokenizer.ggml.tokens
    [<unk> <|start_story|> <|end_story|> ! ...]
  • tokenizer.ggml.unknown_token_id
    0
  • Tensors
  • Name
    Type
    Shape
  • token_embd.weight
    Q8_0
    [128 2048]
  • blk.0
  • blk.0.attn_norm.weight
    F32
    [128]
  • blk.0.ffn_down.weight
    Q8_0
    [384 128]
  • blk.0.ffn_gate.weight
    Q8_0
    [128 384]
  • blk.0.ffn_up.weight
    Q8_0
    [128 384]
  • blk.0.ffn_norm.weight
    F32
    [128]
  • blk.0.attn_k.weight
    Q8_0
    [128 64]
  • blk.0.attn_output.weight
    Q8_0
    [128 128]
  • blk.0.attn_q.weight
    Q8_0
    [128 128]
  • blk.0.attn_v.weight
    Q8_0
    [128 64]
  • blk.1
  • blk.1.attn_norm.weight
    F32
    [128]
  • blk.1.ffn_down.weight
    Q8_0
    [384 128]
  • blk.1.ffn_gate.weight
    Q8_0
    [128 384]
  • blk.1.ffn_up.weight
    Q8_0
    [128 384]
  • blk.1.ffn_norm.weight
    F32
    [128]
  • blk.1.attn_k.weight
    Q8_0
    [128 64]
  • blk.1.attn_output.weight
    Q8_0
    [128 128]
  • blk.1.attn_q.weight
    Q8_0
    [128 128]
  • blk.1.attn_v.weight
    Q8_0
    [128 64]
  • output_norm.weight
    F32
    [128]