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Thox-ai
/
thoxmicro
:1bit-9m
2
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3 weeks ago
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thoxmicro:1bit-9m
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/
model
d33cea1fc823 · 9.8MB
Metadata
general.architecture
llama
llama
general.file_type
Q8_0
Q8_0
llama.attention.head_count
8
8
llama.attention.head_count_kv
8
8
llama.attention.key_length
32
32
llama.attention.layer_norm_rms_epsilon
1e-06
1e-06
llama.attention.value_length
32
32
llama.block_count
8
8
llama.context_length
512
512
llama.embedding_length
256
256
llama.feed_forward_length
768
768
llama.rope.dimension_count
32
32
llama.rope.freq_base
10000
10000
llama.vocab_size
8192
8192
tokenizer.ggml.bos_token_id
1
1
tokenizer.ggml.eos_token_id
2
2
tokenizer.ggml.merges
[h e, Ġ t, Ġ a, Ġ s, Ġ w, ...]
[h e, Ġ t, Ġ a, Ġ s, Ġ w, ...]
tokenizer.ggml.model
gpt2
gpt2
tokenizer.ggml.padding_token_id
0
0
tokenizer.ggml.pre
gpt-2
gpt-2
tokenizer.ggml.token_type
[3, 3, 3, 3, 1, ...]
[3, 3, 3, 3, 1, ...]
tokenizer.ggml.tokens
[<pad>, <bos>, <eos>, <unk>, !, ...]
[<pad>, <bos>, <eos>, <unk>, !, ...]
tokenizer.ggml.unknown_token_id
3
3
Tensor
Name
Type
Shape
token_embd.weight
Q8_0
Q8_0
[256, 8192]
blk.0
blk.0.attn_k.weight
Q8_0
Q8_0
[256, 256]
blk.0.attn_norm.weight
F32
F32
[256]
blk.0.attn_output.weight
Q8_0
Q8_0
[256, 256]
blk.0.attn_q.weight
Q8_0
Q8_0
[256, 256]
blk.0.attn_v.weight
Q8_0
Q8_0
[256, 256]
blk.0.ffn_down.weight
Q8_0
Q8_0
[768, 256]
blk.0.ffn_gate.weight
Q8_0
Q8_0
[256, 768]
blk.0.ffn_norm.weight
F32
F32
[256]
blk.0.ffn_up.weight
Q8_0
Q8_0
[256, 768]
blk.1
blk.1.attn_k.weight
Q8_0
Q8_0
[256, 256]
blk.1.attn_norm.weight
F32
F32
[256]
blk.1.attn_output.weight
Q8_0
Q8_0
[256, 256]
blk.1.attn_q.weight
Q8_0
Q8_0
[256, 256]
blk.1.attn_v.weight
Q8_0
Q8_0
[256, 256]
blk.1.ffn_down.weight
Q8_0
Q8_0
[768, 256]
blk.1.ffn_gate.weight
Q8_0
Q8_0
[256, 768]
blk.1.ffn_norm.weight
F32
F32
[256]
blk.1.ffn_up.weight
Q8_0
Q8_0
[256, 768]
blk.2
blk.2.attn_k.weight
Q8_0
Q8_0
[256, 256]
blk.2.attn_norm.weight
F32
F32
[256]
blk.2.attn_output.weight
Q8_0
Q8_0
[256, 256]
blk.2.attn_q.weight
Q8_0
Q8_0
[256, 256]
blk.2.attn_v.weight
Q8_0
Q8_0
[256, 256]
blk.2.ffn_down.weight
Q8_0
Q8_0
[768, 256]
blk.2.ffn_gate.weight
Q8_0
Q8_0
[256, 768]
blk.2.ffn_norm.weight
F32
F32
[256]
blk.2.ffn_up.weight
Q8_0
Q8_0
[256, 768]
blk.3
blk.3.attn_k.weight
Q8_0
Q8_0
[256, 256]
blk.3.attn_norm.weight
F32
F32
[256]
blk.3.attn_output.weight
Q8_0
Q8_0
[256, 256]
blk.3.attn_q.weight
Q8_0
Q8_0
[256, 256]
blk.3.attn_v.weight
Q8_0
Q8_0
[256, 256]
blk.3.ffn_down.weight
Q8_0
Q8_0
[768, 256]
blk.3.ffn_gate.weight
Q8_0
Q8_0
[256, 768]
blk.3.ffn_norm.weight
F32
F32
[256]
blk.3.ffn_up.weight
Q8_0
Q8_0
[256, 768]
blk.4
blk.4.attn_k.weight
Q8_0
Q8_0
[256, 256]
blk.4.attn_norm.weight
F32
F32
[256]
blk.4.attn_output.weight
Q8_0
Q8_0
[256, 256]
blk.4.attn_q.weight
Q8_0
Q8_0
[256, 256]
blk.4.attn_v.weight
Q8_0
Q8_0
[256, 256]
blk.4.ffn_down.weight
Q8_0
Q8_0
[768, 256]
blk.4.ffn_gate.weight
Q8_0
Q8_0
[256, 768]
blk.4.ffn_norm.weight
F32
F32
[256]
blk.4.ffn_up.weight
Q8_0
Q8_0
[256, 768]
blk.5
blk.5.attn_k.weight
Q8_0
Q8_0
[256, 256]
blk.5.attn_norm.weight
F32
F32
[256]
blk.5.attn_output.weight
Q8_0
Q8_0
[256, 256]
blk.5.attn_q.weight
Q8_0
Q8_0
[256, 256]
blk.5.attn_v.weight
Q8_0
Q8_0
[256, 256]
blk.5.ffn_down.weight
Q8_0
Q8_0
[768, 256]
blk.5.ffn_gate.weight
Q8_0
Q8_0
[256, 768]
blk.5.ffn_norm.weight
F32
F32
[256]
blk.5.ffn_up.weight
Q8_0
Q8_0
[256, 768]
blk.6
blk.6.attn_k.weight
Q8_0
Q8_0
[256, 256]
blk.6.attn_norm.weight
F32
F32
[256]
blk.6.attn_output.weight
Q8_0
Q8_0
[256, 256]
blk.6.attn_q.weight
Q8_0
Q8_0
[256, 256]
blk.6.attn_v.weight
Q8_0
Q8_0
[256, 256]
blk.6.ffn_down.weight
Q8_0
Q8_0
[768, 256]
blk.6.ffn_gate.weight
Q8_0
Q8_0
[256, 768]
blk.6.ffn_norm.weight
F32
F32
[256]
blk.6.ffn_up.weight
Q8_0
Q8_0
[256, 768]
blk.7
blk.7.attn_k.weight
Q8_0
Q8_0
[256, 256]
blk.7.attn_norm.weight
F32
F32
[256]
blk.7.attn_output.weight
Q8_0
Q8_0
[256, 256]
blk.7.attn_q.weight
Q8_0
Q8_0
[256, 256]
blk.7.attn_v.weight
Q8_0
Q8_0
[256, 256]
blk.7.ffn_down.weight
Q8_0
Q8_0
[768, 256]
blk.7.ffn_gate.weight
Q8_0
Q8_0
[256, 768]
blk.7.ffn_norm.weight
F32
F32
[256]
blk.7.ffn_up.weight
Q8_0
Q8_0
[256, 768]
output_norm.weight
F32
F32
[256]