This model was built using the Smaug recipe for improving performance on real world multi-turn conversations applied to meta-llama/Meta-Llama-3-8B-Instruct.
212 Pulls Updated 5 months ago
f284cbdad0fc · 4.4GB
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general.architecturellama
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general.file_type30
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general.name..
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general.quantization_version2
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llama.attention.head_count32
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llama.attention.head_count_kv8
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llama.attention.layer_norm_rms_epsilon1e-05
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llama.block_count32
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llama.context_length8192
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llama.embedding_length4096
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llama.feed_forward_length14336
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llama.rope.dimension_count128
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llama.rope.freq_base500000
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llama.vocab_size128256
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quantize.imatrix.chunks_count88
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quantize.imatrix.dataset/shared/opt/work_models/_imatrix/groups_merged.txt
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quantize.imatrix.entries_count224
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quantize.imatrix.fileimatrix.dat
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tokenizer.ggml.bos_token_id128000
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tokenizer.ggml.eos_token_id128001
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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.padding_token_id128001
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tokenizer.ggml.presmaug-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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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
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