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mannix
/
gemma4-98e-v6-coder
:mtp-Q4_K_M
1,451
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Updated
3 months ago
The best 20b coding model just got better! Beats the bigger 26b brother in Python and code reasoning
The best 20b coding model just got better! Beats the bigger 26b brother in Python and code reasoning
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gemma4-98e-v6-coder:mtp-Q4_K_M
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2a7bc8ed3f50 ยท 446MB
Metadata
general.architecture
gemma4_assistant
gemma4_assistant
general.file_type
Q8_0
Q8_0
gemma4_assistant.attention.head_count
16
16
gemma4_assistant.attention.head_count_kv
[8, 8, 8, 2]
[8, 8, 8, 2]
gemma4_assistant.attention.k_eq_v
true
true
gemma4_assistant.attention.key_length
512
512
gemma4_assistant.attention.key_length_swa
256
256
gemma4_assistant.attention.layer_norm_rms_epsilon
1e-06
1e-06
gemma4_assistant.attention.shared_kv_layers
4
4
gemma4_assistant.attention.sliding_window
1024
1024
gemma4_assistant.attention.sliding_window_pattern
[true, true, true, false]
[true, true, true, false]
gemma4_assistant.attention.value_length
512
512
gemma4_assistant.attention.value_length_swa
256
256
gemma4_assistant.block_count
4
4
gemma4_assistant.centroid_top_k
32
32
gemma4_assistant.context_length
262144
262144
gemma4_assistant.embedding_length
1024
1024
gemma4_assistant.embedding_length_per_layer_input
0
0
gemma4_assistant.feed_forward_length
8192
8192
gemma4_assistant.n_centroids
2048
2048
gemma4_assistant.n_embd_backbone
2816
2816
gemma4_assistant.requires_target_arch
gemma4
gemma4
gemma4_assistant.rope.dimension_count
512
512
gemma4_assistant.rope.dimension_count_swa
256
256
gemma4_assistant.rope.freq_base
1e+06
1e+06
gemma4_assistant.rope.freq_base_swa
10000
10000
gemma4_assistant.use_ordered_embeddings
false
false
gemma4_assistant.vocab_size
262144
262144
tokenizer.ggml.model
none
none
Tensor
Name
Type
Shape
token_embd.weight
Q8_0
Q8_0
[1024, 262144]
blk.0
blk.0.attn_norm.weight
F32
F32
[1024]
blk.0.attn_output.weight
Q8_0
Q8_0
[4096, 1024]
blk.0.attn_q.weight
Q8_0
Q8_0
[1024, 4096]
blk.0.attn_q_norm.weight
F32
F32
[256]
blk.0.ffn_down.weight
Q8_0
Q8_0
[8192, 1024]
blk.0.ffn_gate.weight
Q8_0
Q8_0
[1024, 8192]
blk.0.ffn_norm.weight
F32
F32
[1024]
blk.0.ffn_up.weight
Q8_0
Q8_0
[1024, 8192]
blk.0.layer_output_scale.weight
F32
F32
[1]
blk.0.post_attention_norm.weight
F32
F32
[1024]
blk.0.post_ffw_norm.weight
F32
F32
[1024]
blk.1
blk.1.attn_norm.weight
F32
F32
[1024]
blk.1.attn_output.weight
Q8_0
Q8_0
[4096, 1024]
blk.1.attn_q.weight
Q8_0
Q8_0
[1024, 4096]
blk.1.attn_q_norm.weight
F32
F32
[256]
blk.1.ffn_down.weight
Q8_0
Q8_0
[8192, 1024]
blk.1.ffn_gate.weight
Q8_0
Q8_0
[1024, 8192]
blk.1.ffn_norm.weight
F32
F32
[1024]
blk.1.ffn_up.weight
Q8_0
Q8_0
[1024, 8192]
blk.1.layer_output_scale.weight
F32
F32
[1]
blk.1.post_attention_norm.weight
F32
F32
[1024]
blk.1.post_ffw_norm.weight
F32
F32
[1024]
blk.2
blk.2.attn_norm.weight
F32
F32
[1024]
blk.2.attn_output.weight
Q8_0
Q8_0
[4096, 1024]
blk.2.attn_q.weight
Q8_0
Q8_0
[1024, 4096]
blk.2.attn_q_norm.weight
F32
F32
[256]
blk.2.ffn_down.weight
Q8_0
Q8_0
[8192, 1024]
blk.2.ffn_gate.weight
Q8_0
Q8_0
[1024, 8192]
blk.2.ffn_norm.weight
F32
F32
[1024]
blk.2.ffn_up.weight
Q8_0
Q8_0
[1024, 8192]
blk.2.layer_output_scale.weight
F32
F32
[1]
blk.2.post_attention_norm.weight
F32
F32
[1024]
blk.2.post_ffw_norm.weight
F32
F32
[1024]
blk.3
blk.3.attn_norm.weight
F32
F32
[1024]
blk.3.attn_output.weight
Q8_0
Q8_0
[8192, 1024]
blk.3.attn_q.weight
Q8_0
Q8_0
[1024, 8192]
blk.3.attn_q_norm.weight
F32
F32
[512]
blk.3.ffn_down.weight
Q8_0
Q8_0
[8192, 1024]
blk.3.ffn_gate.weight
Q8_0
Q8_0
[1024, 8192]
blk.3.ffn_norm.weight
F32
F32
[1024]
blk.3.ffn_up.weight
Q8_0
Q8_0
[1024, 8192]
blk.3.layer_output_scale.weight
F32
F32
[1]
blk.3.post_attention_norm.weight
F32
F32
[1024]
blk.3.post_ffw_norm.weight
F32
F32
[1024]
mtp.post_projection.weight
Q8_0
Q8_0
[1024, 2816]
mtp.pre_projection.weight
Q8_0
Q8_0
[5632, 1024]
rope_freqs.weight
F32
F32
[256]
output_norm.weight
F32
F32
[1024]