numind/ nuextract3:Q6_K

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NuExtract3 is a 4B vision-language reasoning model by NuMind for local document understanding. Turn text and document images into structured JSON or clean Markdown with Ollama, with support for multilingual documents, OCR, and template generation.

vision tools thinking
... /
projector
9a506ce43544 · 676MB
    Metadata
  • general.architecture
    clip
  • general.file_type
    BF16
  • clip.has_vision_encoder
    true
  • clip.projector_type
    qwen3vl_merger
  • clip.use_gelu
    true
  • clip.vision.attention.head_count
    16
  • clip.vision.attention.layer_norm_epsilon
    1e-06
  • clip.vision.block_count
    24
  • clip.vision.embedding_length
    1024
  • clip.vision.feed_forward_length
    4096
  • clip.vision.image_mean
    [0.5, 0.5, 0.5]
  • clip.vision.image_size
    768
  • clip.vision.image_std
    [0.5, 0.5, 0.5]
  • clip.vision.is_deepstack_layers
    [false, false, false, false, false, ...]
  • clip.vision.patch_size
    16
  • clip.vision.projection_dim
    2560
  • clip.vision.spatial_merge_size
    2
    • Tensor
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    [4096, 1024]
  • v.blk.22.ffn_up.bias
    F32
    [4096]
  • v.blk.22.ffn_up.weight
    BF16
    [1024, 4096]
  • v.blk.22.ln1.bias
    F32
    [1024]
  • v.blk.22.ln1.weight
    F32
    [1024]
  • v.blk.22.ln2.bias
    F32
    [1024]
  • v.blk.22.ln2.weight
    F32
    [1024]
    • v.blk.23
  • v.blk.23.attn_out.bias
    F32
    [1024]
  • v.blk.23.attn_out.weight
    BF16
    [1024, 1024]
  • v.blk.23.attn_qkv.bias
    F32
    [3072]
  • v.blk.23.attn_qkv.weight
    BF16
    [1024, 3072]
  • v.blk.23.ffn_down.bias
    F32
    [1024]
  • v.blk.23.ffn_down.weight
    BF16
    [4096, 1024]
  • v.blk.23.ffn_up.bias
    F32
    [4096]
  • v.blk.23.ffn_up.weight
    BF16
    [1024, 4096]
  • v.blk.23.ln1.bias
    F32
    [1024]
  • v.blk.23.ln1.weight
    F32
    [1024]
  • v.blk.23.ln2.bias
    F32
    [1024]
  • v.blk.23.ln2.weight
    F32
    [1024]
  • v.patch_embd.bias
    F32
    [1024]
  • v.patch_embd.weight
    F32
    [16, 16, 3, 1024]
  • v.patch_embd.weight.1
    F32
    [16, 16, 3, 1024]
  • v.position_embd.weight
    F32
    [1024, 2304]
  • v.post_ln.bias
    F32
    [1024]
  • v.post_ln.weight
    F32
    [1024]