EXAONE 3.5 is a collection of instruction-tuned bilingual (English and Korean) generative models ranging from 2.4B to 32B parameters, developed and released by LG AI Research.
2.4b
7.8b
32b
3,977 Pulls Updated 13 days ago
a92c55b71e45 · 19GB
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exaone.attention.head_count40
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exaone.attention.head_count_kv8
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exaone.attention.layer_norm_rms_epsilon1e-05
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exaone.block_count64
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exaone.context_length32768
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exaone.embedding_length5120
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exaone.feed_forward_length27392
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exaone.rope.dimension_count128
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exaone.rope.freq_base1e+06
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general.architectureexaone
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general.basenameEXAONE-3.5
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general.file_type15
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general.finetuneInstruct
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general.languages[en, ko]
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general.licenseother
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general.license.linkLICENSE
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general.license.nameexaone
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general.nameEXAONE 3.5 32B Instruct
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general.quantization_version2
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general.size_label32B
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general.tags[lg-ai, exaone, exaone-3.5, text-generation]
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general.typemodel
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tokenizer.ggml.bos_token_id1
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tokenizer.ggml.eos_token_id361
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tokenizer.ggml.merges[t h, Ġ a, Ġ í, i n, Ġ th, ...]
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tokenizer.ggml.modelgpt2
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tokenizer.ggml.padding_token_id0
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tokenizer.ggml.preexaone
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tokenizer.ggml.token_type[3, 3, 3, 3, 4, ...]
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tokenizer.ggml.tokens[[PAD], [BOS], [EOS], [UNK], , ...]
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tokenizer.ggml.unknown_token_id3
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NameTypeShape
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token_embd.weightQ4_K[5120, 102400]
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blk.0.attn_k.weightQ4_K[5120, 1024]
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blk.34.attn_k.weightQ4_K[5120, 1024]
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blk.34.attn_norm.weightF32[5120]
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blk.34.attn_q.weightQ4_K[5120, 5120]
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blk.34.attn_v.weightQ6_K[5120, 1024]
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blk.34.ffn_down.weightQ6_K[27392, 5120]
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blk.34.ffn_gate.weightQ4_K[5120, 27392]
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blk.34.ffn_norm.weightF32[5120]
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blk.34.ffn_up.weightQ4_K[5120, 27392]
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blk.35.attn_k.weightQ4_K[5120, 1024]
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blk.35.attn_norm.weightF32[5120]
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blk.35.attn_output.weightQ4_K[5120, 5120]
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blk.35.attn_q.weightQ4_K[5120, 5120]
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blk.35.attn_v.weightQ4_K[5120, 1024]
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blk.35.ffn_down.weightQ4_K[27392, 5120]
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blk.35.ffn_gate.weightQ4_K[5120, 27392]
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blk.35.ffn_norm.weightF32[5120]
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blk.35.ffn_up.weightQ4_K[5120, 27392]
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blk.36.attn_k.weightQ4_K[5120, 1024]
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blk.36.attn_norm.weightF32[5120]
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blk.36.attn_output.weightQ4_K[5120, 5120]
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blk.36.attn_q.weightQ4_K[5120, 5120]
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blk.36.attn_v.weightQ4_K[5120, 1024]
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blk.36.ffn_down.weightQ4_K[27392, 5120]
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blk.36.ffn_gate.weightQ4_K[5120, 27392]
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blk.36.ffn_norm.weightF32[5120]
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blk.36.ffn_up.weightQ4_K[5120, 27392]
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blk.37.attn_k.weightQ4_K[5120, 1024]
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blk.37.attn_norm.weightF32[5120]
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blk.37.attn_output.weightQ4_K[5120, 5120]
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blk.37.attn_q.weightQ4_K[5120, 5120]
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blk.37.attn_v.weightQ6_K[5120, 1024]
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blk.37.ffn_down.weightQ6_K[27392, 5120]
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blk.37.ffn_gate.weightQ4_K[5120, 27392]
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blk.37.ffn_norm.weightF32[5120]
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blk.37.ffn_up.weightQ4_K[5120, 27392]
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blk.38.attn_k.weightQ4_K[5120, 1024]
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blk.38.attn_norm.weightF32[5120]
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blk.38.attn_output.weightQ4_K[5120, 5120]
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blk.38.attn_q.weightQ4_K[5120, 5120]
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blk.38.attn_v.weightQ4_K[5120, 1024]
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blk.38.ffn_down.weightQ4_K[27392, 5120]
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blk.38.ffn_gate.weightQ4_K[5120, 27392]
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blk.38.ffn_norm.weightF32[5120]
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blk.38.ffn_up.weightQ4_K[5120, 27392]
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blk.39.attn_k.weightQ4_K[5120, 1024]
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blk.39.attn_norm.weightF32[5120]
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blk.39.attn_output.weightQ4_K[5120, 5120]
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blk.39.attn_q.weightQ4_K[5120, 5120]
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blk.39.attn_v.weightQ4_K[5120, 1024]
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blk.39.ffn_down.weightQ4_K[27392, 5120]
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blk.39.ffn_gate.weightQ4_K[5120, 27392]
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blk.39.ffn_norm.weightF32[5120]
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blk.39.ffn_up.weightQ4_K[5120, 27392]
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blk.40.attn_k.weightQ4_K[5120, 1024]
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blk.40.attn_norm.weightF32[5120]
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blk.40.attn_output.weightQ4_K[5120, 5120]
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blk.40.attn_q.weightQ4_K[5120, 5120]
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blk.40.attn_v.weightQ6_K[5120, 1024]
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blk.40.ffn_down.weightQ6_K[27392, 5120]
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blk.40.ffn_gate.weightQ4_K[5120, 27392]
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blk.40.ffn_norm.weightF32[5120]
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blk.40.ffn_up.weightQ4_K[5120, 27392]
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blk.41.attn_k.weightQ4_K[5120, 1024]
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blk.41.attn_norm.weightF32[5120]
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blk.41.attn_output.weightQ4_K[5120, 5120]
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blk.41.attn_q.weightQ4_K[5120, 5120]
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blk.41.attn_v.weightQ4_K[5120, 1024]
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blk.41.ffn_down.weightQ4_K[27392, 5120]
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blk.41.ffn_gate.weightQ4_K[5120, 27392]
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blk.41.ffn_norm.weightF32[5120]
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blk.41.ffn_up.weightQ4_K[5120, 27392]
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blk.42.attn_k.weightQ4_K[5120, 1024]
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blk.42.attn_norm.weightF32[5120]
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blk.42.attn_output.weightQ4_K[5120, 5120]
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blk.42.attn_q.weightQ4_K[5120, 5120]
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blk.42.attn_v.weightQ4_K[5120, 1024]
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blk.42.ffn_down.weightQ4_K[27392, 5120]
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blk.42.ffn_gate.weightQ4_K[5120, 27392]
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blk.42.ffn_norm.weightF32[5120]
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blk.42.ffn_up.weightQ4_K[5120, 27392]
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blk.43.attn_k.weightQ4_K[5120, 1024]
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blk.43.attn_norm.weightF32[5120]
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blk.43.attn_output.weightQ4_K[5120, 5120]
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blk.43.attn_q.weightQ4_K[5120, 5120]
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blk.43.attn_v.weightQ6_K[5120, 1024]
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blk.43.ffn_down.weightQ6_K[27392, 5120]
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blk.43.ffn_gate.weightQ4_K[5120, 27392]
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blk.43.ffn_norm.weightF32[5120]
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blk.43.ffn_up.weightQ4_K[5120, 27392]
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blk.44.attn_k.weightQ4_K[5120, 1024]
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blk.44.attn_norm.weightF32[5120]
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blk.44.attn_output.weightQ4_K[5120, 5120]
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blk.44.attn_q.weightQ4_K[5120, 5120]
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blk.44.attn_v.weightQ4_K[5120, 1024]
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blk.44.ffn_down.weightQ4_K[27392, 5120]
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blk.44.ffn_gate.weightQ4_K[5120, 27392]
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blk.44.ffn_norm.weightF32[5120]
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blk.44.ffn_up.weightQ4_K[5120, 27392]
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blk.45.attn_k.weightQ4_K[5120, 1024]
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blk.45.attn_norm.weightF32[5120]
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blk.45.attn_output.weightQ4_K[5120, 5120]
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blk.45.attn_q.weightQ4_K[5120, 5120]
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blk.45.attn_v.weightQ4_K[5120, 1024]
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blk.45.ffn_down.weightQ4_K[27392, 5120]
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blk.45.ffn_gate.weightQ4_K[5120, 27392]
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blk.45.ffn_norm.weightF32[5120]
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blk.45.ffn_up.weightQ4_K[5120, 27392]
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blk.46.attn_k.weightQ4_K[5120, 1024]
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blk.46.attn_norm.weightF32[5120]
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blk.46.attn_output.weightQ4_K[5120, 5120]
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blk.46.attn_q.weightQ4_K[5120, 5120]
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blk.46.attn_v.weightQ6_K[5120, 1024]
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blk.46.ffn_down.weightQ6_K[27392, 5120]
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blk.46.ffn_gate.weightQ4_K[5120, 27392]
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blk.46.ffn_norm.weightF32[5120]
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blk.46.ffn_up.weightQ4_K[5120, 27392]
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blk.47.attn_k.weightQ4_K[5120, 1024]
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blk.47.attn_norm.weightF32[5120]
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blk.47.attn_q.weightQ4_K[5120, 5120]
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blk.47.attn_v.weightQ4_K[5120, 1024]
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blk.47.ffn_down.weightQ4_K[27392, 5120]
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blk.47.ffn_gate.weightQ4_K[5120, 27392]
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blk.47.ffn_norm.weightF32[5120]
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blk.47.ffn_up.weightQ4_K[5120, 27392]
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blk.48.attn_k.weightQ4_K[5120, 1024]
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blk.48.attn_norm.weightF32[5120]
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blk.48.attn_q.weightQ4_K[5120, 5120]
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blk.48.attn_v.weightQ4_K[5120, 1024]
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blk.48.ffn_down.weightQ4_K[27392, 5120]
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blk.48.ffn_gate.weightQ4_K[5120, 27392]
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blk.48.ffn_norm.weightF32[5120]
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blk.48.ffn_up.weightQ4_K[5120, 27392]
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blk.49.attn_k.weightQ4_K[5120, 1024]
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blk.49.attn_norm.weightF32[5120]
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blk.49.attn_output.weightQ4_K[5120, 5120]
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blk.49.attn_q.weightQ4_K[5120, 5120]
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blk.49.attn_v.weightQ6_K[5120, 1024]
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blk.49.ffn_down.weightQ6_K[27392, 5120]
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blk.49.ffn_gate.weightQ4_K[5120, 27392]
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blk.49.ffn_norm.weightF32[5120]
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blk.49.ffn_up.weightQ4_K[5120, 27392]
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blk.50.attn_k.weightQ4_K[5120, 1024]
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blk.50.attn_norm.weightF32[5120]
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blk.50.attn_output.weightQ4_K[5120, 5120]
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blk.50.attn_q.weightQ4_K[5120, 5120]
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blk.50.attn_v.weightQ4_K[5120, 1024]
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blk.50.ffn_down.weightQ4_K[27392, 5120]
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blk.50.ffn_gate.weightQ4_K[5120, 27392]
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blk.50.ffn_norm.weightF32[5120]
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blk.50.ffn_up.weightQ4_K[5120, 27392]
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blk.51.attn_k.weightQ4_K[5120, 1024]
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blk.51.attn_norm.weightF32[5120]
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blk.51.attn_q.weightQ4_K[5120, 5120]
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blk.51.attn_v.weightQ4_K[5120, 1024]
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blk.51.ffn_down.weightQ4_K[27392, 5120]
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blk.51.ffn_gate.weightQ4_K[5120, 27392]
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blk.51.ffn_norm.weightF32[5120]
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blk.51.ffn_up.weightQ4_K[5120, 27392]
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blk.52.attn_k.weightQ4_K[5120, 1024]
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blk.52.attn_norm.weightF32[5120]
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blk.52.attn_q.weightQ4_K[5120, 5120]
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blk.52.ffn_down.weightQ6_K[27392, 5120]
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blk.52.ffn_gate.weightQ4_K[5120, 27392]
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blk.52.ffn_norm.weightF32[5120]
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blk.52.ffn_up.weightQ4_K[5120, 27392]
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blk.53.attn_k.weightQ4_K[5120, 1024]
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blk.53.attn_norm.weightF32[5120]
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blk.53.attn_output.weightQ4_K[5120, 5120]
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blk.53.attn_q.weightQ4_K[5120, 5120]
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blk.53.attn_v.weightQ4_K[5120, 1024]
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blk.53.ffn_gate.weightQ4_K[5120, 27392]
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blk.53.ffn_norm.weightF32[5120]
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blk.53.ffn_up.weightQ4_K[5120, 27392]
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blk.54.attn_k.weightQ4_K[5120, 1024]
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blk.54.attn_norm.weightF32[5120]
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blk.54.attn_output.weightQ4_K[5120, 5120]
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blk.54.attn_q.weightQ4_K[5120, 5120]
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blk.54.attn_v.weightQ4_K[5120, 1024]
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blk.54.ffn_down.weightQ4_K[27392, 5120]
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blk.54.ffn_gate.weightQ4_K[5120, 27392]
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blk.54.ffn_norm.weightF32[5120]
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blk.54.ffn_up.weightQ4_K[5120, 27392]
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blk.55.attn_k.weightQ4_K[5120, 1024]
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blk.55.attn_norm.weightF32[5120]
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blk.55.attn_output.weightQ4_K[5120, 5120]
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blk.55.attn_q.weightQ4_K[5120, 5120]
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blk.55.ffn_down.weightQ6_K[27392, 5120]
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blk.55.ffn_gate.weightQ4_K[5120, 27392]
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blk.55.ffn_norm.weightF32[5120]
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blk.56.attn_k.weightQ4_K[5120, 1024]
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blk.56.attn_norm.weightF32[5120]
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blk.56.attn_q.weightQ4_K[5120, 5120]
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blk.56.attn_v.weightQ6_K[5120, 1024]
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blk.56.ffn_down.weightQ6_K[27392, 5120]
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blk.56.ffn_gate.weightQ4_K[5120, 27392]
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blk.56.ffn_norm.weightF32[5120]
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blk.56.ffn_up.weightQ4_K[5120, 27392]
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blk.57.attn_k.weightQ4_K[5120, 1024]
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blk.57.attn_norm.weightF32[5120]
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blk.57.attn_q.weightQ4_K[5120, 5120]
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blk.57.attn_v.weightQ6_K[5120, 1024]
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blk.57.ffn_down.weightQ6_K[27392, 5120]
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blk.57.ffn_gate.weightQ4_K[5120, 27392]
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blk.57.ffn_norm.weightF32[5120]
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blk.57.ffn_up.weightQ4_K[5120, 27392]
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blk.58.attn_k.weightQ4_K[5120, 1024]
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blk.58.attn_norm.weightF32[5120]
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blk.58.attn_q.weightQ4_K[5120, 5120]
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blk.58.ffn_down.weightQ6_K[27392, 5120]
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blk.58.ffn_gate.weightQ4_K[5120, 27392]
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blk.58.ffn_norm.weightF32[5120]
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blk.58.ffn_up.weightQ4_K[5120, 27392]
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blk.59.attn_k.weightQ4_K[5120, 1024]
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blk.59.attn_norm.weightF32[5120]
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blk.59.attn_q.weightQ4_K[5120, 5120]
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blk.59.attn_v.weightQ6_K[5120, 1024]
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blk.59.ffn_down.weightQ6_K[27392, 5120]
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blk.59.ffn_gate.weightQ4_K[5120, 27392]
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blk.59.ffn_norm.weightF32[5120]
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blk.60.attn_k.weightQ4_K[5120, 1024]
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blk.60.attn_norm.weightF32[5120]
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blk.60.attn_q.weightQ4_K[5120, 5120]
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blk.60.attn_v.weightQ6_K[5120, 1024]
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blk.60.ffn_norm.weightF32[5120]
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blk.61.attn_k.weightQ4_K[5120, 1024]
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blk.61.attn_norm.weightF32[5120]
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blk.61.attn_q.weightQ4_K[5120, 5120]
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blk.61.attn_v.weightQ6_K[5120, 1024]
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blk.61.ffn_down.weightQ6_K[27392, 5120]
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blk.61.ffn_gate.weightQ4_K[5120, 27392]
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blk.61.ffn_norm.weightF32[5120]
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blk.61.ffn_up.weightQ4_K[5120, 27392]
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blk.62.attn_k.weightQ4_K[5120, 1024]
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blk.62.attn_norm.weightF32[5120]
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blk.62.attn_output.weightQ4_K[5120, 5120]
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blk.62.attn_q.weightQ4_K[5120, 5120]
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blk.62.ffn_down.weightQ6_K[27392, 5120]
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blk.62.ffn_gate.weightQ4_K[5120, 27392]
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blk.62.ffn_norm.weightF32[5120]
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blk.62.ffn_up.weightQ4_K[5120, 27392]
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blk.63.attn_k.weightQ4_K[5120, 1024]
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blk.63.attn_norm.weightF32[5120]
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blk.63.attn_output.weightQ4_K[5120, 5120]
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blk.63.attn_q.weightQ4_K[5120, 5120]
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blk.63.attn_v.weightQ6_K[5120, 1024]
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blk.63.ffn_down.weightQ6_K[27392, 5120]
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blk.63.ffn_gate.weightQ4_K[5120, 27392]
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blk.63.ffn_norm.weightF32[5120]
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blk.63.ffn_up.weightQ4_K[5120, 27392]
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output.weightQ6_K[5120, 102400]
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rope_freqs.weightF32[64]
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output_norm.weightF32[5120]
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
blk.18
blk.19
blk.20
blk.21
blk.22
blk.23
blk.24
blk.25
blk.26
blk.27
blk.28
blk.29
blk.30
blk.31
blk.32
blk.33
blk.34
blk.35
blk.36
blk.37
blk.38
blk.39
blk.40
blk.41
blk.42
blk.43
blk.44
blk.45
blk.46
blk.47
blk.48
blk.49
blk.50
blk.51
blk.52
blk.53
blk.54
blk.55
blk.56
blk.57
blk.58
blk.59
blk.60
blk.61
blk.62
blk.63