JXW67/ TGAI_NB:3b

21 1 week ago

TGAI NB — a lightweight Chinese MoE chat model family, built end-to-end by a high school student. V2 (3B): 8-expert sparse MoE, better quality for desktop. V1 (0.86B): 4-expert sparse MoE, ultra-light, smooth on low-end devices.

0.86b 3b
... /
model
c1dee6dbfd82 · 5.9GB
    Metadata
  • general.architecture
    llama
  • general.file_type
    F16
  • llama.attention.head_count
    16
  • llama.attention.head_count_kv
    16
  • llama.attention.layer_norm_rms_epsilon
    1e-06
  • llama.block_count
    28
  • llama.context_length
    512
  • llama.embedding_length
    1024
  • llama.expert_count
    8
  • llama.expert_used_count
    2
  • llama.feed_forward_length
    4096
  • llama.rope.freq_base
    10000
  • llama.vocab_size
    8668
  • tokenizer.ggml.add_bos_token
    true
  • tokenizer.ggml.add_eos_token
    false
  • tokenizer.ggml.add_space_prefix
    false
  • tokenizer.ggml.bos_token_id
    2
  • tokenizer.ggml.byte_fallback
    false
  • tokenizer.ggml.eos_token_id
    3
  • tokenizer.ggml.merges
    []
  • tokenizer.ggml.model
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  • tokenizer.ggml.scores
    [0, 0, 0, 0, 0, ...]
  • tokenizer.ggml.tokens
    [<PAD>, <UNK>, <BOS>, <EOS>, <IMG>, ...]
  • tokenizer.ggml.unk_token_id
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    • Tensor
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  • blk.24.ffn_up_exps.weight
    F16
    [1024, 4096, 8]
    • blk.25
  • blk.25.attn_k.weight
    F16
    [1024, 1024]
  • blk.25.attn_norm.weight
    F32
    [1024]
  • blk.25.attn_output.weight
    F16
    [1024, 1024]
  • blk.25.attn_q.weight
    F16
    [1024, 1024]
  • blk.25.attn_v.weight
    F16
    [1024, 1024]
  • blk.25.ffn_down_exps.weight
    F16
    [4096, 1024, 8]
  • blk.25.ffn_gate_exps.weight
    F16
    [1024, 4096, 8]
  • blk.25.ffn_gate_inp.weight
    F16
    [1024, 8]
  • blk.25.ffn_norm.weight
    F32
    [1024]
  • blk.25.ffn_up_exps.weight
    F16
    [1024, 4096, 8]
    • blk.26
  • blk.26.attn_k.weight
    F16
    [1024, 1024]
  • blk.26.attn_norm.weight
    F32
    [1024]
  • blk.26.attn_output.weight
    F16
    [1024, 1024]
  • blk.26.attn_q.weight
    F16
    [1024, 1024]
  • blk.26.attn_v.weight
    F16
    [1024, 1024]
  • blk.26.ffn_down_exps.weight
    F16
    [4096, 1024, 8]
  • blk.26.ffn_gate_exps.weight
    F16
    [1024, 4096, 8]
  • blk.26.ffn_gate_inp.weight
    F16
    [1024, 8]
  • blk.26.ffn_norm.weight
    F32
    [1024]
  • blk.26.ffn_up_exps.weight
    F16
    [1024, 4096, 8]
    • blk.27
  • blk.27.attn_k.weight
    F16
    [1024, 1024]
  • blk.27.attn_norm.weight
    F32
    [1024]
  • blk.27.attn_output.weight
    F16
    [1024, 1024]
  • blk.27.attn_q.weight
    F16
    [1024, 1024]
  • blk.27.attn_v.weight
    F16
    [1024, 1024]
  • blk.27.ffn_down_exps.weight
    F16
    [4096, 1024, 8]
  • blk.27.ffn_gate_exps.weight
    F16
    [1024, 4096, 8]
  • blk.27.ffn_gate_inp.weight
    F16
    [1024, 8]
  • blk.27.ffn_norm.weight
    F32
    [1024]
  • blk.27.ffn_up_exps.weight
    F16
    [1024, 4096, 8]
  • output_norm.weight
    F32
    [1024]