Gemma is a family of lightweight, state-of-the-art open models built by Google DeepMind. Updated to version 1.1
2b
7b
4.2M Pulls Updated 8 months ago
c6a572b250cb · 1.3GB
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gemma.attention.head_count8
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gemma.attention.head_count_kv1
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gemma.attention.key_length256
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gemma.attention.layer_norm_rms_epsilon1e-06
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gemma.attention.value_length256
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gemma.block_count18
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gemma.context_length8192
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gemma.embedding_length2048
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gemma.feed_forward_length16384
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general.architecturegemma
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general.file_type10
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general.namegemma-2b
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general.quantization_version2
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tokenizer.ggml.bos_token_id2
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tokenizer.ggml.eos_token_id1
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tokenizer.ggml.modelllama
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tokenizer.ggml.padding_token_id0
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tokenizer.ggml.scores[0, 0, 0, 0, 0, ...]
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tokenizer.ggml.token_type[3, 3, 3, 2, 1, ...]
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tokenizer.ggml.tokens[<pad>, <eos>, <bos>, <unk>, <mask>, ...]
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tokenizer.ggml.unknown_token_id3
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NameTypeShape
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blk.0.attn_norm.weightF32[2048]
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blk.0.attn_output.weightQ3_K[2048, 2048]
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blk.0.ffn_gate.weightQ2_K[2048, 16384]
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blk.0.ffn_norm.weightF32[2048]
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blk.0.ffn_up.weightQ2_K[2048, 16384]
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blk.1.attn_norm.weightF32[2048]
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blk.1.attn_output.weightQ3_K[2048, 2048]
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blk.1.attn_q.weightQ2_K[2048, 2048]
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blk.1.attn_v.weightQ4_K[2048, 256]
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blk.1.ffn_down.weightQ3_K[16384, 2048]
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blk.1.ffn_gate.weightQ2_K[2048, 16384]
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blk.1.ffn_norm.weightF32[2048]
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blk.1.ffn_up.weightQ2_K[2048, 16384]
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blk.2.attn_k.weightQ2_K[2048, 256]
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blk.2.attn_norm.weightF32[2048]
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blk.2.attn_output.weightQ3_K[2048, 2048]
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blk.2.attn_q.weightQ2_K[2048, 2048]
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blk.2.attn_v.weightQ4_K[2048, 256]
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blk.2.ffn_down.weightQ3_K[16384, 2048]
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blk.2.ffn_gate.weightQ2_K[2048, 16384]
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blk.2.ffn_norm.weightF32[2048]
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blk.2.ffn_up.weightQ2_K[2048, 16384]
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blk.3.attn_norm.weightF32[2048]
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blk.3.attn_output.weightQ3_K[2048, 2048]
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blk.3.attn_q.weightQ2_K[2048, 2048]
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blk.3.ffn_norm.weightF32[2048]
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blk.4.attn_norm.weightF32[2048]
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blk.4.ffn_norm.weightF32[2048]
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blk.5.attn_norm.weightF32[2048]
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blk.5.attn_q.weightQ2_K[2048, 2048]
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blk.5.ffn_norm.weightF32[2048]
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blk.6.attn_q.weightQ2_K[2048, 2048]
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blk.6.ffn_down.weightQ3_K[16384, 2048]
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blk.6.ffn_gate.weightQ2_K[2048, 16384]
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blk.6.ffn_norm.weightF32[2048]
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blk.6.ffn_up.weightQ2_K[2048, 16384]
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blk.7.attn_k.weightQ2_K[2048, 256]
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blk.7.attn_norm.weightF32[2048]
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blk.7.attn_output.weightQ3_K[2048, 2048]
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blk.7.attn_q.weightQ2_K[2048, 2048]
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blk.7.attn_v.weightQ4_K[2048, 256]
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blk.7.ffn_norm.weightF32[2048]
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blk.8.attn_norm.weightF32[2048]
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blk.8.attn_q.weightQ2_K[2048, 2048]
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blk.8.attn_v.weightQ4_K[2048, 256]
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blk.8.ffn_down.weightQ3_K[16384, 2048]
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blk.8.ffn_gate.weightQ2_K[2048, 16384]
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blk.8.ffn_norm.weightF32[2048]
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blk.8.ffn_up.weightQ2_K[2048, 16384]
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blk.9.attn_k.weightQ2_K[2048, 256]
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blk.9.attn_norm.weightF32[2048]
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blk.9.attn_output.weightQ3_K[2048, 2048]
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blk.9.attn_q.weightQ2_K[2048, 2048]
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blk.9.ffn_down.weightQ3_K[16384, 2048]
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blk.9.ffn_gate.weightQ2_K[2048, 16384]
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blk.9.ffn_norm.weightF32[2048]
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blk.9.ffn_up.weightQ2_K[2048, 16384]
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blk.10.attn_k.weightQ2_K[2048, 256]
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blk.10.attn_norm.weightF32[2048]
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blk.10.ffn_norm.weightF32[2048]
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blk.11.attn_norm.weightF32[2048]
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blk.11.attn_q.weightQ2_K[2048, 2048]
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blk.11.attn_v.weightQ4_K[2048, 256]
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blk.11.ffn_norm.weightF32[2048]
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blk.11.ffn_up.weightQ2_K[2048, 16384]
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blk.12.attn_k.weightQ2_K[2048, 256]
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blk.12.attn_norm.weightF32[2048]
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blk.12.attn_output.weightQ3_K[2048, 2048]
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blk.12.attn_q.weightQ2_K[2048, 2048]
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blk.12.attn_v.weightQ4_K[2048, 256]
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blk.12.ffn_down.weightQ3_K[16384, 2048]
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blk.12.ffn_norm.weightF32[2048]
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blk.13.ffn_gate.weightQ2_K[2048, 16384]
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blk.13.ffn_norm.weightF32[2048]
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blk.13.ffn_up.weightQ2_K[2048, 16384]
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blk.14.attn_norm.weightF32[2048]
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blk.14.attn_q.weightQ2_K[2048, 2048]
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blk.14.ffn_norm.weightF32[2048]
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blk.14.ffn_up.weightQ2_K[2048, 16384]
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blk.15.attn_norm.weightF32[2048]
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blk.15.attn_output.weightQ3_K[2048, 2048]
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blk.15.attn_q.weightQ2_K[2048, 2048]
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blk.15.attn_v.weightQ4_K[2048, 256]
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blk.15.ffn_norm.weightF32[2048]
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blk.15.ffn_up.weightQ2_K[2048, 16384]
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blk.16.attn_norm.weightF32[2048]
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blk.16.ffn_norm.weightF32[2048]
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blk.16.ffn_up.weightQ2_K[2048, 16384]
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blk.17.attn_k.weightQ2_K[2048, 256]
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blk.17.attn_norm.weightF32[2048]
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blk.17.attn_output.weightQ3_K[2048, 2048]
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blk.17.attn_q.weightQ2_K[2048, 2048]
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blk.17.attn_v.weightQ4_K[2048, 256]
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blk.17.ffn_gate.weightQ2_K[2048, 16384]
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blk.17.ffn_norm.weightF32[2048]
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blk.17.ffn_up.weightQ2_K[2048, 16384]
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output_norm.weightF32[2048]
Metadata
Tensor
blk.0
blk.1
blk.2
blk.3
blk.4
blk.5
blk.6
blk.7
blk.8
blk.9
blk.10
blk.11
blk.12
blk.13
blk.14
blk.15
blk.16
blk.17