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s1gnature
/
gemma4-uncensored-mtp
:e2b-q4_k_m
1,383
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Updated
4 days ago
Uncensored Gemma 4 E4B & E2B (0/465 refusals) with MTP drafter. 32k context, up to 80 TPS on RTX 3050 8GB.
Uncensored Gemma 4 E4B & E2B (0/465 refusals) with MTP drafter. 32k context, up to 80 TPS on RTX 3050 8GB.
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gemma4-uncensored-mtp:e2b-q4_k_m
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2e58a8dcb7c4 · 170MB
Metadata
general.architecture
gemma4-assistant
gemma4-assistant
general.file_type
F16
F16
gemma4-assistant.attention.head_count
4
4
gemma4-assistant.attention.head_count_kv
1
1
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
512
512
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.context_length
131072
131072
gemma4-assistant.embedding_length
256
256
gemma4-assistant.embedding_length_out
1536
1536
gemma4-assistant.embedding_length_per_layer_input
0
0
gemma4-assistant.feed_forward_length
2048
2048
gemma4-assistant.nextn_predict_layers
4
4
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
tokenizer.ggml.add_bos_token
true
true
tokenizer.ggml.add_space_prefix
false
false
tokenizer.ggml.bos_token_id
2
2
tokenizer.ggml.eos_token_id
1
1
tokenizer.ggml.mask_token_id
4
4
tokenizer.ggml.merges
[ , ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ ▁, , , ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ ▁▁, ...]
[ , ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ ▁, , , ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ ▁▁, ...]
tokenizer.ggml.model
gemma4
gemma4
tokenizer.ggml.padding_token_id
0
0
tokenizer.ggml.scores
[-1000, -1000, -1000, -1000, -1000, ...]
[-1000, -1000, -1000, -1000, -1000, ...]
tokenizer.ggml.token_type
[3, 3, 3, 3, 3, ...]
[3, 3, 3, 3, 3, ...]
tokenizer.ggml.tokens
[<pad>, <eos>, <bos>, <unk>, <mask>, ...]
[<pad>, <eos>, <bos>, <unk>, <mask>, ...]
tokenizer.ggml.unknown_token_id
3
3
Tensor
Name
Type
Shape
token_embd.weight
F16
F16
[256, 262144]
blk.0
blk.0.attn_norm.weight
F32
F32
[256]
blk.0.attn_output.weight
F16
F16
[1024, 256]
blk.0.attn_q.weight
F16
F16
[256, 1024]
blk.0.attn_q_norm.weight
F32
F32
[256]
blk.0.ffn_down.weight
F16
F16
[2048, 256]
blk.0.ffn_gate.weight
F16
F16
[256, 2048]
blk.0.ffn_norm.weight
F32
F32
[256]
blk.0.ffn_up.weight
F16
F16
[256, 2048]
blk.0.layer_output_scale.weight
F32
F32
[1]
blk.0.post_attention_norm.weight
F32
F32
[256]
blk.0.post_ffw_norm.weight
F32
F32
[256]
blk.1
blk.1.attn_norm.weight
F32
F32
[256]
blk.1.attn_output.weight
F16
F16
[1024, 256]
blk.1.attn_q.weight
F16
F16
[256, 1024]
blk.1.attn_q_norm.weight
F32
F32
[256]
blk.1.ffn_down.weight
F16
F16
[2048, 256]
blk.1.ffn_gate.weight
F16
F16
[256, 2048]
blk.1.ffn_norm.weight
F32
F32
[256]
blk.1.ffn_up.weight
F16
F16
[256, 2048]
blk.1.layer_output_scale.weight
F32
F32
[1]
blk.1.post_attention_norm.weight
F32
F32
[256]
blk.1.post_ffw_norm.weight
F32
F32
[256]
blk.2
blk.2.attn_norm.weight
F32
F32
[256]
blk.2.attn_output.weight
F16
F16
[1024, 256]
blk.2.attn_q.weight
F16
F16
[256, 1024]
blk.2.attn_q_norm.weight
F32
F32
[256]
blk.2.ffn_down.weight
F16
F16
[2048, 256]
blk.2.ffn_gate.weight
F16
F16
[256, 2048]
blk.2.ffn_norm.weight
F32
F32
[256]
blk.2.ffn_up.weight
F16
F16
[256, 2048]
blk.2.layer_output_scale.weight
F32
F32
[1]
blk.2.post_attention_norm.weight
F32
F32
[256]
blk.2.post_ffw_norm.weight
F32
F32
[256]
blk.3
blk.3.attn_norm.weight
F32
F32
[256]
blk.3.attn_output.weight
F16
F16
[2048, 256]
blk.3.attn_q.weight
F16
F16
[256, 2048]
blk.3.attn_q_norm.weight
F32
F32
[512]
blk.3.ffn_down.weight
F16
F16
[2048, 256]
blk.3.ffn_gate.weight
F16
F16
[256, 2048]
blk.3.ffn_norm.weight
F32
F32
[256]
blk.3.ffn_up.weight
F16
F16
[256, 2048]
blk.3.layer_output_scale.weight
F32
F32
[1]
blk.3.post_attention_norm.weight
F32
F32
[256]
blk.3.post_ffw_norm.weight
F32
F32
[256]
nextn.post_projection.weight
F16
F16
[256, 1536]
nextn.pre_projection.weight
F16
F16
[3072, 256]
rope_freqs.weight
F32
F32
[256]
output_norm.weight
F32
F32
[256]