nchapman/
ministral-8b-instruct-2410

Ministral 8B is an 8B parameter model featuring a unique interleaved sliding-window attention pattern for faster, memory-efficient inference. Designed for edge use cases, it supports up to 128k context length and excels in knowledge and reasoning tasks.

tools 8b

324 2 months ago

2 Tags
... /
model
bbe8d91c1964 · 4.9GB
    Metadata
  • general.architecture
    llama
  • general.file_type
    Q4_K_M
  • llama.attention.head_count
    32
  • llama.attention.head_count_kv
    8
  • llama.attention.key_length
    128
  • llama.attention.layer_norm_rms_epsilon
    1e-05
  • llama.attention.value_length
    128
  • llama.block_count
    36
  • llama.context_length
    32768
  • llama.embedding_length
    4096
  • llama.feed_forward_length
    12288
  • llama.rope.dimension_count
    128
  • llama.rope.freq_base
    1e+08
  • llama.vocab_size
    131072
  • quantize.imatrix.chunks_count
    128
  • quantize.imatrix.dataset
    /training_dir/calibration_datav3.txt
  • quantize.imatrix.entries_count
    252
  • quantize.imatrix.file
    /models_out/Ministral-8B-Instruct-2410-TEST-GGUF/Ministral-8B-Instruct-2410-TEST.imatrix
  • tokenizer.ggml.add_bos_token
    true
  • tokenizer.ggml.add_eos_token
    false
  • tokenizer.ggml.add_space_prefix
    false
  • tokenizer.ggml.bos_token_id
    1
  • tokenizer.ggml.eos_token_id
    2
  • tokenizer.ggml.merges
    [Ġ Ġ, Ġ t, e r, i n, Ġ ĠĠĠ, ...]
  • tokenizer.ggml.model
    gpt2
  • tokenizer.ggml.pre
    tekken
  • tokenizer.ggml.token_type
    [3, 3, 3, 3, 3, ...]
  • tokenizer.ggml.tokens
    [<unk>, <s>, </s>, [INST], [/INST], ...]
  • tokenizer.ggml.unknown_token_id
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  • blk.26.attn_norm.weight
    F32
    [4096]
  • blk.26.attn_output.weight
    Q4_K
    [4096, 4096]
  • blk.26.attn_q.weight
    Q4_K
    [4096, 4096]
  • blk.26.attn_v.weight
    Q4_K
    [4096, 1024]
  • blk.26.ffn_down.weight
    Q4_K
    [12288, 4096]
  • blk.26.ffn_gate.weight
    Q4_K
    [4096, 12288]
  • blk.26.ffn_norm.weight
    F32
    [4096]
  • blk.26.ffn_up.weight
    Q4_K
    [4096, 12288]
    • blk.27
  • blk.27.attn_k.weight
    Q4_K
    [4096, 1024]
  • blk.27.attn_norm.weight
    F32
    [4096]
  • blk.27.attn_output.weight
    Q4_K
    [4096, 4096]
  • blk.27.attn_q.weight
    Q4_K
    [4096, 4096]
  • blk.27.attn_v.weight
    Q6_K
    [4096, 1024]
  • blk.27.ffn_down.weight
    Q6_K
    [12288, 4096]
  • blk.27.ffn_gate.weight
    Q4_K
    [4096, 12288]
  • blk.27.ffn_norm.weight
    F32
    [4096]
  • blk.27.ffn_up.weight
    Q4_K
    [4096, 12288]
    • blk.28
  • blk.28.attn_k.weight
    Q4_K
    [4096, 1024]
  • blk.28.attn_norm.weight
    F32
    [4096]
  • blk.28.attn_output.weight
    Q4_K
    [4096, 4096]
  • blk.28.attn_q.weight
    Q4_K
    [4096, 4096]
  • blk.28.attn_v.weight
    Q4_K
    [4096, 1024]
  • blk.28.ffn_down.weight
    Q4_K
    [12288, 4096]
  • blk.28.ffn_gate.weight
    Q4_K
    [4096, 12288]
  • blk.28.ffn_norm.weight
    F32
    [4096]
  • blk.28.ffn_up.weight
    Q4_K
    [4096, 12288]
    • blk.29
  • blk.29.attn_k.weight
    Q4_K
    [4096, 1024]
  • blk.29.attn_norm.weight
    F32
    [4096]
  • blk.29.attn_output.weight
    Q4_K
    [4096, 4096]
  • blk.29.attn_q.weight
    Q4_K
    [4096, 4096]
  • blk.29.attn_v.weight
    Q4_K
    [4096, 1024]
  • blk.29.ffn_down.weight
    Q4_K
    [12288, 4096]
  • blk.29.ffn_gate.weight
    Q4_K
    [4096, 12288]
  • blk.29.ffn_norm.weight
    F32
    [4096]
  • blk.29.ffn_up.weight
    Q4_K
    [4096, 12288]
    • blk.30
  • blk.30.attn_k.weight
    Q4_K
    [4096, 1024]
  • blk.30.attn_norm.weight
    F32
    [4096]
  • blk.30.attn_output.weight
    Q4_K
    [4096, 4096]
  • blk.30.attn_q.weight
    Q4_K
    [4096, 4096]
  • blk.30.attn_v.weight
    Q6_K
    [4096, 1024]
  • blk.30.ffn_down.weight
    Q6_K
    [12288, 4096]
  • blk.30.ffn_gate.weight
    Q4_K
    [4096, 12288]
  • blk.30.ffn_norm.weight
    F32
    [4096]
  • blk.30.ffn_up.weight
    Q4_K
    [4096, 12288]
    • blk.31
  • blk.31.attn_k.weight
    Q4_K
    [4096, 1024]
  • blk.31.attn_norm.weight
    F32
    [4096]
  • blk.31.attn_output.weight
    Q4_K
    [4096, 4096]
  • blk.31.attn_q.weight
    Q4_K
    [4096, 4096]
  • blk.31.attn_v.weight
    Q6_K
    [4096, 1024]
  • blk.31.ffn_down.weight
    Q6_K
    [12288, 4096]
  • blk.31.ffn_gate.weight
    Q4_K
    [4096, 12288]
  • blk.31.ffn_norm.weight
    F32
    [4096]
  • blk.31.ffn_up.weight
    Q4_K
    [4096, 12288]
    • blk.32
  • blk.32.attn_k.weight
    Q4_K
    [4096, 1024]
  • blk.32.attn_norm.weight
    F32
    [4096]
  • blk.32.attn_output.weight
    Q4_K
    [4096, 4096]
  • blk.32.attn_q.weight
    Q4_K
    [4096, 4096]
  • blk.32.attn_v.weight
    Q6_K
    [4096, 1024]
  • blk.32.ffn_down.weight
    Q6_K
    [12288, 4096]
  • blk.32.ffn_gate.weight
    Q4_K
    [4096, 12288]
  • blk.32.ffn_norm.weight
    F32
    [4096]
  • blk.32.ffn_up.weight
    Q4_K
    [4096, 12288]
    • blk.33
  • blk.33.attn_k.weight
    Q4_K
    [4096, 1024]
  • blk.33.attn_norm.weight
    F32
    [4096]
  • blk.33.attn_output.weight
    Q4_K
    [4096, 4096]
  • blk.33.attn_q.weight
    Q4_K
    [4096, 4096]
  • blk.33.attn_v.weight
    Q6_K
    [4096, 1024]
  • blk.33.ffn_down.weight
    Q6_K
    [12288, 4096]
  • blk.33.ffn_gate.weight
    Q4_K
    [4096, 12288]
  • blk.33.ffn_norm.weight
    F32
    [4096]
  • blk.33.ffn_up.weight
    Q4_K
    [4096, 12288]
    • blk.34
  • blk.34.attn_k.weight
    Q4_K
    [4096, 1024]
  • blk.34.attn_norm.weight
    F32
    [4096]
  • blk.34.attn_output.weight
    Q4_K
    [4096, 4096]
  • blk.34.attn_q.weight
    Q4_K
    [4096, 4096]
  • blk.34.attn_v.weight
    Q6_K
    [4096, 1024]
  • blk.34.ffn_down.weight
    Q6_K
    [12288, 4096]
  • blk.34.ffn_gate.weight
    Q4_K
    [4096, 12288]
  • blk.34.ffn_norm.weight
    F32
    [4096]
  • blk.34.ffn_up.weight
    Q4_K
    [4096, 12288]
    • blk.35
  • blk.35.attn_k.weight
    Q4_K
    [4096, 1024]
  • blk.35.attn_norm.weight
    F32
    [4096]
  • blk.35.attn_output.weight
    Q4_K
    [4096, 4096]
  • blk.35.attn_q.weight
    Q4_K
    [4096, 4096]
  • blk.35.attn_v.weight
    Q6_K
    [4096, 1024]
  • blk.35.ffn_down.weight
    Q6_K
    [12288, 4096]
  • blk.35.ffn_gate.weight
    Q4_K
    [4096, 12288]
  • blk.35.ffn_norm.weight
    F32
    [4096]
  • blk.35.ffn_up.weight
    Q4_K
    [4096, 12288]
  • output.weight
    Q6_K
    [4096, 131072]
  • output_norm.weight
    F32
    [4096]