Meta's Llama 3.2 goes small with 1B and 3B models.
tools
1b
3b
3.2M Pulls Updated 8 weeks ago
74701a8c35f6 · 1.3GB
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general.architecturellama
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general.basenameLlama-3.2
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general.file_type7
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general.finetuneInstruct
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general.languages[en, de, fr, it, pt, ...]
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general.nameLlama 3.2 1B Instruct
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general.quantization_version2
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general.size_label1B
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general.tags[facebook, meta, pytorch, llama, llama-3, ...]
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general.typemodel
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llama.attention.head_count32
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llama.attention.head_count_kv8
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llama.attention.key_length64
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llama.attention.layer_norm_rms_epsilon1e-05
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llama.attention.value_length64
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llama.block_count16
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llama.context_length131072
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llama.embedding_length2048
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llama.feed_forward_length8192
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llama.rope.dimension_count64
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llama.rope.freq_base500000
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llama.vocab_size128256
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tokenizer.ggml.bos_token_id128000
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tokenizer.ggml.eos_token_id128009
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tokenizer.ggml.merges[Ġ Ġ, Ġ ĠĠĠ, ĠĠ ĠĠ, ĠĠĠ Ġ, i n, ...]
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tokenizer.ggml.modelgpt2
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tokenizer.ggml.prellama-bpe
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tokenizer.ggml.token_type[1, 1, 1, 1, 1, ...]
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tokenizer.ggml.tokens[!, ", #, $, %, ...]
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NameTypeShape
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blk.0.attn_k.weightQ8_0[2048, 512]
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blk.0.attn_norm.weightF32[2048]
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blk.0.attn_output.weightQ8_0[2048, 2048]
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blk.0.attn_q.weightQ8_0[2048, 2048]
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blk.0.attn_v.weightQ8_0[2048, 512]
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blk.0.ffn_down.weightQ8_0[8192, 2048]
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blk.0.ffn_gate.weightQ8_0[2048, 8192]
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blk.0.ffn_norm.weightF32[2048]
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blk.0.ffn_up.weightQ8_0[2048, 8192]
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blk.1.attn_k.weightQ8_0[2048, 512]
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blk.1.attn_norm.weightF32[2048]
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blk.1.attn_output.weightQ8_0[2048, 2048]
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blk.1.attn_q.weightQ8_0[2048, 2048]
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blk.1.attn_v.weightQ8_0[2048, 512]
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blk.1.ffn_down.weightQ8_0[8192, 2048]
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blk.1.ffn_gate.weightQ8_0[2048, 8192]
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blk.1.ffn_norm.weightF32[2048]
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blk.1.ffn_up.weightQ8_0[2048, 8192]
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blk.2.attn_k.weightQ8_0[2048, 512]
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blk.2.attn_norm.weightF32[2048]
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blk.2.attn_output.weightQ8_0[2048, 2048]
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blk.2.attn_q.weightQ8_0[2048, 2048]
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blk.2.attn_v.weightQ8_0[2048, 512]
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blk.2.ffn_down.weightQ8_0[8192, 2048]
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blk.2.ffn_gate.weightQ8_0[2048, 8192]
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blk.2.ffn_norm.weightF32[2048]
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blk.2.ffn_up.weightQ8_0[2048, 8192]
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blk.3.attn_k.weightQ8_0[2048, 512]
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blk.3.attn_norm.weightF32[2048]
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blk.3.attn_output.weightQ8_0[2048, 2048]
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blk.3.attn_q.weightQ8_0[2048, 2048]
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blk.3.attn_v.weightQ8_0[2048, 512]
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blk.3.ffn_gate.weightQ8_0[2048, 8192]
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blk.3.ffn_norm.weightF32[2048]
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blk.3.ffn_up.weightQ8_0[2048, 8192]
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blk.4.attn_k.weightQ8_0[2048, 512]
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blk.4.attn_norm.weightF32[2048]
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blk.4.attn_q.weightQ8_0[2048, 2048]
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blk.4.attn_v.weightQ8_0[2048, 512]
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blk.4.ffn_down.weightQ8_0[8192, 2048]
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blk.4.ffn_gate.weightQ8_0[2048, 8192]
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blk.4.ffn_norm.weightF32[2048]
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blk.4.ffn_up.weightQ8_0[2048, 8192]
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blk.5.attn_k.weightQ8_0[2048, 512]
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blk.5.attn_norm.weightF32[2048]
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blk.5.attn_q.weightQ8_0[2048, 2048]
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blk.5.attn_v.weightQ8_0[2048, 512]
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blk.5.ffn_down.weightQ8_0[8192, 2048]
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blk.6.attn_norm.weightF32[2048]
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blk.6.ffn_gate.weightQ8_0[2048, 8192]
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blk.6.ffn_norm.weightF32[2048]
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blk.6.ffn_up.weightQ8_0[2048, 8192]
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blk.7.attn_k.weightQ8_0[2048, 512]
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blk.7.attn_norm.weightF32[2048]
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blk.7.attn_q.weightQ8_0[2048, 2048]
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blk.7.attn_v.weightQ8_0[2048, 512]
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blk.7.ffn_norm.weightF32[2048]
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blk.7.ffn_up.weightQ8_0[2048, 8192]
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blk.8.attn_k.weightQ8_0[2048, 512]
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blk.8.attn_norm.weightF32[2048]
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blk.8.attn_output.weightQ8_0[2048, 2048]
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blk.8.attn_q.weightQ8_0[2048, 2048]
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blk.8.attn_v.weightQ8_0[2048, 512]
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blk.8.ffn_down.weightQ8_0[8192, 2048]
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blk.8.ffn_gate.weightQ8_0[2048, 8192]
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blk.8.ffn_norm.weightF32[2048]
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blk.8.ffn_up.weightQ8_0[2048, 8192]
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blk.9.attn_k.weightQ8_0[2048, 512]
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blk.9.attn_norm.weightF32[2048]
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blk.9.ffn_norm.weightF32[2048]
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blk.9.ffn_up.weightQ8_0[2048, 8192]
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blk.10.attn_norm.weightF32[2048]
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blk.11.ffn_norm.weightF32[2048]
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blk.12.attn_norm.weightF32[2048]
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blk.12.attn_q.weightQ8_0[2048, 2048]
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blk.12.attn_v.weightQ8_0[2048, 512]
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blk.12.ffn_norm.weightF32[2048]
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blk.12.ffn_up.weightQ8_0[2048, 8192]
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blk.13.attn_norm.weightF32[2048]
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blk.13.attn_q.weightQ8_0[2048, 2048]
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blk.13.attn_v.weightQ8_0[2048, 512]
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blk.13.ffn_gate.weightQ8_0[2048, 8192]
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blk.13.ffn_norm.weightF32[2048]
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blk.13.ffn_up.weightQ8_0[2048, 8192]
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blk.14.attn_k.weightQ8_0[2048, 512]
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blk.14.attn_norm.weightF32[2048]
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blk.14.ffn_norm.weightF32[2048]
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blk.15.attn_norm.weightF32[2048]
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blk.15.attn_q.weightQ8_0[2048, 2048]
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blk.15.ffn_norm.weightF32[2048]
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blk.15.ffn_up.weightQ8_0[2048, 8192]
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rope_freqs.weightF32[32]
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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