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TCYZ
/
nano
:latest
11
Downloads
Updated
2 months ago
Model şu an beta aşamasındadır. 1M parametrenin getirdiği sınırlardan dolayı karmaşık cümle yapılarında bozulmalar yaşanabilir. Geliştirme süreci devam etmektedir.
Model şu an beta aşamasındadır. 1M parametrenin getirdiği sınırlardan dolayı karmaşık cümle yapılarında bozulmalar yaşanabilir. Geliştirme süreci devam etmektedir.
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1m
1.2m
nano:latest
...
/
model
810d4b136236 · 4.3MB
Metadata
general.architecture
llama
llama
llama.attention.head_count
4
4
llama.attention.head_count_kv
4
4
llama.attention.layer_norm_rms_epsilon
1e-06
1e-06
llama.block_count
5
5
llama.context_length
64
64
llama.embedding_length
128
128
llama.feed_forward_length
256
256
llama.rope.dimension_count
32
32
tokenizer.ggml.bos_token_id
0
0
tokenizer.ggml.eos_token_id
2
2
tokenizer.ggml.merges
[Ä ±, o r, Ġ b, a n, e r, ...]
[Ä ±, o r, Ġ b, a n, e r, ...]
tokenizer.ggml.model
gpt2
gpt2
tokenizer.ggml.padding_token_id
1
1
tokenizer.ggml.tokens
[<s>, <pad>, </s>, <unk>, <mask>, ...]
[<s>, <pad>, </s>, <unk>, <mask>, ...]
Tensor
Name
Type
Shape
token_embd.weight
F32
F32
[128, 1000]
blk.0
blk.0.attn_k.weight
F32
F32
[128, 128]
blk.0.attn_norm.weight
F32
F32
[128]
blk.0.attn_output.weight
F32
F32
[128, 128]
blk.0.attn_q.weight
F32
F32
[128, 128]
blk.0.attn_v.weight
F32
F32
[128, 128]
blk.0.ffn_down.weight
F32
F32
[256, 128]
blk.0.ffn_gate.weight
F32
F32
[128, 256]
blk.0.ffn_norm.weight
F32
F32
[128]
blk.0.ffn_up.weight
F32
F32
[128, 256]
blk.1
blk.1.attn_k.weight
F32
F32
[128, 128]
blk.1.attn_norm.weight
F32
F32
[128]
blk.1.attn_output.weight
F32
F32
[128, 128]
blk.1.attn_q.weight
F32
F32
[128, 128]
blk.1.attn_v.weight
F32
F32
[128, 128]
blk.1.ffn_down.weight
F32
F32
[256, 128]
blk.1.ffn_gate.weight
F32
F32
[128, 256]
blk.1.ffn_norm.weight
F32
F32
[128]
blk.1.ffn_up.weight
F32
F32
[128, 256]
blk.2
blk.2.attn_k.weight
F32
F32
[128, 128]
blk.2.attn_norm.weight
F32
F32
[128]
blk.2.attn_output.weight
F32
F32
[128, 128]
blk.2.attn_q.weight
F32
F32
[128, 128]
blk.2.attn_v.weight
F32
F32
[128, 128]
blk.2.ffn_down.weight
F32
F32
[256, 128]
blk.2.ffn_gate.weight
F32
F32
[128, 256]
blk.2.ffn_norm.weight
F32
F32
[128]
blk.2.ffn_up.weight
F32
F32
[128, 256]
blk.3
blk.3.attn_k.weight
F32
F32
[128, 128]
blk.3.attn_norm.weight
F32
F32
[128]
blk.3.attn_output.weight
F32
F32
[128, 128]
blk.3.attn_q.weight
F32
F32
[128, 128]
blk.3.attn_v.weight
F32
F32
[128, 128]
blk.3.ffn_down.weight
F32
F32
[256, 128]
blk.3.ffn_gate.weight
F32
F32
[128, 256]
blk.3.ffn_norm.weight
F32
F32
[128]
blk.3.ffn_up.weight
F32
F32
[128, 256]
blk.4
blk.4.attn_k.weight
F32
F32
[128, 128]
blk.4.attn_norm.weight
F32
F32
[128]
blk.4.attn_output.weight
F32
F32
[128, 128]
blk.4.attn_q.weight
F32
F32
[128, 128]
blk.4.attn_v.weight
F32
F32
[128, 128]
blk.4.ffn_down.weight
F32
F32
[256, 128]
blk.4.ffn_gate.weight
F32
F32
[128, 256]
blk.4.ffn_norm.weight
F32
F32
[128]
blk.4.ffn_up.weight
F32
F32
[128, 256]
output.weight
F32
F32
[128, 1000]
output_norm.weight
F32
F32
[128]