expand further, be pickier
This commit is contained in:
parent
e66f80a819
commit
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3 changed files with 435 additions and 15 deletions
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@ -1,19 +1,72 @@
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# frozen_string_literal: true
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MIN_8S = 0
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require 'digest'
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MIN_8S = 5
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def expand(set)
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cased = set + set.map(&:downcase) + set.map(&:upcase)
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spaced = cased + cased.map { _1.gsub(/\s/, ' ') } + cased.map { _1.gsub(/\s/, "\n") } + cased.flat_map do |amulet|
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20.times.map { amulet.gsub(/\s/) { rand(2).zero? ? ' ' : "\n" } }
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end
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spaced + spaced.flat_map { _1.match?(/[.?!]$/) ? [_1.gsub('.', '?'), _1.gsub('?', '.')] : ["#{_1}.", "#{_1}?"] }
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end
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def max_8s(str)
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(str.scan(/8+/).max || '').length
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end
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$stdin.read.split('poem: ')
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existing = Set[
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"If you can't write poems,
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write me",
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"IN THE SPRING MY LUNGS
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STILL SOMEHOW EXPAND.",
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"A MAN ONCE MAILED ME
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A PIECE OF HIS HEART",
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"THIS AMULET
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AT ANY PRICE
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FELT LIKE THE TRUTH",
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"this amulet is a simple token which proves my love's truth",
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"DON'T WORRY.",
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"in the early hours of the new year
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i lie on my back
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waiting.",
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"All my life I had this
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image of what a poet
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should be",
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'chaiyya chaiyya',
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'THE REAL AMULET IS THE FRIENDS WE MADE ALONG THE WAY*',
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'Winter evening, a leaf, a blue sky above.',
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'Lethargically good.',
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'An amulet is a self-aware house?',
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"Ever Tried Ever Failed
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Try Again Fail Again. find your amulet",
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'the wind at night has a dream',
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"the wind:
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don't ask me what it is",
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'a certain wind, to blow this back to me',
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]
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existing = expand existing
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poems = $stdin.read.split('poem: ')
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.map(&:strip)
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.reject(&:empty?)
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.to_set
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.map { [_1, `printf "#{_1}" | openssl sha256`.strip] }
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poems = expand(poems) - existing
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amulets = poems
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.map { [_1, Digest::SHA256.hexdigest(_1)] }
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.filter { |(_, hash)| max_8s(hash) >= MIN_8S }
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.sort_by { |(_, hash)| max_8s hash }
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.each do |(amulet, hash)|
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puts "#{amulets.length}/#{poems.length} poems were amulets"
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puts
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amulets.each do |(amulet, hash)|
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puts amulet
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puts
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puts "#{max_8s hash} #{hash}#{amulet.length > 64 ? ' too long!' : ''}"
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end
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puts
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end
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342
main.log
Normal file
342
main.log
Normal file
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@ -0,0 +1,342 @@
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Cmd: /Users/clark/Downloads/Meta-Llama-3-8B-Instruct.Q5_K_M.llamafile -m Meta-Llama-3-8B-Instruct.Q5_K_M.gguf -c 2048 --no-display-prompt --gpu APPLE -n 256 -p "poem: the cold is here
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poem: the seasons change.
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poem: this amulet is a simple token which proves my love's truth
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poem: It weighs on me.
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poem: If you can't write poems,
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write me
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poem: THIS AMULET
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AT ANY PRICE
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FELT LIKE THE TRUTH
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poem: sphinx of black quartz, judge my vow
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poem: IN THE SPRING MY LUNGS
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STILL SOMEHOW EXPAND.
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poem: DON'T WORRY.
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poem: The air is light, and the air is cold.
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poem: Lethargically good.
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poem: Winter evening, a leaf, a blue sky above.
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poem: A MAN ONCE MAILED ME
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A PIECE OF HIS HEART
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poem: I saw a flower.
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poem: dream, love, exist.
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poem: some flowers grow so quickly
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poem: All my life I had this
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image of what a poet
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should be
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poem: there is a bird, a tree, and a squirrel
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poem: What is an amulet?
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poem: Remember the rain.
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poem: in the early hours of the new year
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i lie on my back
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waiting.
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poem:"
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main: seed = 1731608392
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main: llama backend init
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main: load the model and apply lora adapter, if any
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llama_model_loader: loaded meta data with 21 key-value pairs and 291 tensors from Meta-Llama-3-8B-Instruct.Q5_K_M.gguf (version GGUF V3 (latest))
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llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
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llama_model_loader: - kv 0: general.architecture str = llama
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llama_model_loader: - kv 1: llama.block_count u32 = 32
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llama_model_loader: - kv 2: llama.context_length u32 = 8192
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llama_model_loader: - kv 3: llama.embedding_length u32 = 4096
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llama_model_loader: - kv 4: llama.feed_forward_length u32 = 14336
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llama_model_loader: - kv 5: llama.attention.head_count u32 = 32
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llama_model_loader: - kv 6: llama.attention.head_count_kv u32 = 8
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llama_model_loader: - kv 7: llama.rope.freq_base f32 = 500000.000000
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llama_model_loader: - kv 8: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
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llama_model_loader: - kv 9: general.file_type u32 = 17
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llama_model_loader: - kv 10: llama.vocab_size u32 = 128256
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llama_model_loader: - kv 11: llama.rope.dimension_count u32 = 128
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llama_model_loader: - kv 12: tokenizer.ggml.model str = gpt2
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llama_model_loader: - kv 13: tokenizer.ggml.pre str = llama-bpe
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llama_model_loader: - kv 14: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ...
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llama_model_loader: - kv 15: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
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llama_model_loader: - kv 16: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
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llama_model_loader: - kv 17: tokenizer.ggml.bos_token_id u32 = 128000
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llama_model_loader: - kv 18: tokenizer.ggml.eos_token_id u32 = 128009
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llama_model_loader: - kv 19: tokenizer.chat_template str = {% set loop_messages = messages %}{% ...
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llama_model_loader: - kv 20: general.quantization_version u32 = 2
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llama_model_loader: - type f32: 65 tensors
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llama_model_loader: - type q5_K: 193 tensors
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llama_model_loader: - type q6_K: 33 tensors
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llm_load_vocab: special tokens definition check successful ( 256/128256 ).
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llm_load_print_meta: format = GGUF V3 (latest)
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llm_load_print_meta: arch = llama
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llm_load_print_meta: vocab type = BPE
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llm_load_print_meta: n_vocab = 128256
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llm_load_print_meta: n_merges = 280147
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llm_load_print_meta: n_ctx_train = 8192
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llm_load_print_meta: n_embd = 4096
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llm_load_print_meta: n_head = 32
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llm_load_print_meta: n_head_kv = 8
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llm_load_print_meta: n_layer = 32
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llm_load_print_meta: n_rot = 128
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llm_load_print_meta: n_swa = 0
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llm_load_print_meta: n_embd_head_k = 128
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llm_load_print_meta: n_embd_head_v = 128
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llm_load_print_meta: n_gqa = 4
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llm_load_print_meta: n_embd_k_gqa = 1024
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llm_load_print_meta: n_embd_v_gqa = 1024
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llm_load_print_meta: f_norm_eps = 0.0e+00
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llm_load_print_meta: f_norm_rms_eps = 1.0e-05
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llm_load_print_meta: f_clamp_kqv = 0.0e+00
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llm_load_print_meta: f_max_alibi_bias = 0.0e+00
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llm_load_print_meta: f_logit_scale = 0.0e+00
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llm_load_print_meta: n_ff = 14336
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llm_load_print_meta: n_expert = 0
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llm_load_print_meta: n_expert_used = 0
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llm_load_print_meta: causal attn = 1
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llm_load_print_meta: pooling type = 0
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llm_load_print_meta: rope type = 0
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llm_load_print_meta: rope scaling = linear
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llm_load_print_meta: freq_base_train = 500000.0
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llm_load_print_meta: freq_scale_train = 1
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llm_load_print_meta: n_yarn_orig_ctx = 8192
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llm_load_print_meta: rope_finetuned = unknown
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llm_load_print_meta: ssm_d_conv = 0
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llm_load_print_meta: ssm_d_inner = 0
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llm_load_print_meta: ssm_d_state = 0
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llm_load_print_meta: ssm_dt_rank = 0
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llm_load_print_meta: model type = 8B
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llm_load_print_meta: model ftype = Q5_K - Medium
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llm_load_print_meta: model params = 8.03 B
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llm_load_print_meta: model size = 5.33 GiB (5.70 BPW)
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llm_load_print_meta: general.name = n/a
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llm_load_print_meta: BOS token = 128000 '<|begin_of_text|>'
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llm_load_print_meta: EOS token = 128009 '<|eot_id|>'
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llm_load_print_meta: LF token = 128 'Ä'
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llm_load_print_meta: EOT token = 128009 '<|eot_id|>'
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llm_load_tensors: ggml ctx size = 0.34 MiB
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llm_load_tensors: offloading 32 repeating layers to GPU
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llm_load_tensors: offloaded 32/33 layers to GPU
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llm_load_tensors: Metal buffer size = 5115.48 MiB
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llm_load_tensors: CPU buffer size = 5459.93 MiB
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........................................................................................
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llama_new_context_with_model: n_ctx = 2048
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llama_new_context_with_model: n_batch = 2048
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llama_new_context_with_model: n_ubatch = 512
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llama_new_context_with_model: flash_attn = 0
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llama_new_context_with_model: freq_base = 500000.0
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llama_new_context_with_model: freq_scale = 1
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llama_kv_cache_init: Metal KV buffer size = 256.00 MiB
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llama_new_context_with_model: KV self size = 256.00 MiB, K (f16): 128.00 MiB, V (f16): 128.00 MiB
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llama_new_context_with_model: CPU output buffer size = 0.49 MiB
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llama_new_context_with_model: Metal compute buffer size = 164.00 MiB
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llama_new_context_with_model: CPU compute buffer size = 258.50 MiB
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llama_new_context_with_model: graph nodes = 1030
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llama_new_context_with_model: graph splits = 3
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warming up the model with an empty run
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n_ctx: 2048
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system_info: n_threads = 5 / 11 | AVX = 0 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 |
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add_bos: 0
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tokenize the prompt
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prompt: "poem: the cold is here
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poem: the seasons change.
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poem: this amulet is a simple token which proves my love's truth
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poem: It weighs on me.
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poem: If you can't write poems,
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write me
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poem: THIS AMULET
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AT ANY PRICE
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FELT LIKE THE TRUTH
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poem: sphinx of black quartz, judge my vow
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poem: IN THE SPRING MY LUNGS
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STILL SOMEHOW EXPAND.
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poem: DON'T WORRY.
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poem: The air is light, and the air is cold.
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poem: Lethargically good.
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poem: Winter evening, a leaf, a blue sky above.
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poem: A MAN ONCE MAILED ME
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A PIECE OF HIS HEART
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poem: I saw a flower.
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poem: dream, love, exist.
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poem: some flowers grow so quickly
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poem: All my life I had this
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image of what a poet
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should be
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poem: there is a bird, a tree, and a squirrel
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poem: What is an amulet?
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poem: Remember the rain.
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poem: in the early hours of the new year
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i lie on my back
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waiting.
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poem:"
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tokens: [ '<|begin_of_text|>':128000, 'po':5481, 'em':336, ':':25, ' the':279, ' cold':9439, ' is':374, ' here':1618, '':198, 'po':5481, 'em':336, ':':25, ' the':279, ' seasons':15956, ' change':2349, '.':627, 'po':5481, 'em':336, ':':25, ' this':420, ' am':1097, 'ulet':49518, ' is':374, ' a':264, ' simple':4382, ' token':4037, ' which':902, ' proves':36862, ' my':856, ' love':3021, ''s':596, ' truth':8206, '':198, 'po':5481, 'em':336, ':':25, ' It':1102, ' weighs':50542, ' on':389, ' me':757, '.':627, 'po':5481, 'em':336, ':':25, ' If':1442, ' you':499, ' can':649, ''t':956, ' write':3350, ' poems':45319, ',':345, 'write':5040, ' me':757, '':198, 'po':5481, 'em':336, ':':25, ' THIS':10245, ' AM':6912, 'ULE':7873, 'T':51, '':198, 'AT':835, ' ANY':4230, ' PRICE':60152, '':198, 'F':37, 'EL':2818, 'T':51, ' LIKE':21170, ' THE':3247, ' TR':5091, 'UTH':9331, '':198, 'po':5481, 'em':336, ':':25, ' sph':42822, 'inx':20612, ' of':315, ' black':3776, ' quartz':52255, ',':11, ' judge':11913, ' my':856, ' vow':40443, '':198, 'po':5481, 'em':336, ':':25, ' IN':2006, ' THE':3247, ' SPR':52367, 'ING':1753, ' MY':18725, ' L':445, 'UN':1899, 'GS':16929, '':198, 'ST':790, 'ILL':9410, ' SOME':66655, 'HOW':61297, ' EXP':13768, 'AND':4064, '.':627, 'po':5481, 'em':336, ':':25, ' DON':45373, ''T':17773, ' W':468, 'OR':878, 'RY':11492, '.':627, 'po':5481, 'em':336, ':':25, ' The':578, ' air':3805, ' is':374, ' light':3177, ',':11, ' and':323, ' the':279, ' air':3805, ' is':374, ' cold':9439, '.':627, 'po':5481, 'em':336, ':':25, ' L':445, 'eth':774, 'arg':867, 'ically':2740, ' good':1695, '.':627, 'po':5481, 'em':336, ':':25, ' Winter':20704, ' evening':11714, ',':11, ' a':264, ' leaf':16312, ',':11, ' a':264, ' blue':6437, ' sky':13180, ' above':3485, '.':627, 'po':5481, 'em':336, ':':25, ' A':362, ' MAN':26819, ' ON':6328, 'CE':2152, ' MA':9917, 'ILED':14873, ' ME':16691, '':198, 'A':32, ' PIE':80555, 'CE':2152, ' OF':3083, ' HIS':66226, ' HE':11947, 'ART':3065, '':198, 'po':5481, 'em':336, ':':25, ' I':358, ' saw':5602, ' a':264, ' flower':23153, '.':627, 'po':5481, 'em':336, ':':25, ' dream':8063, ',':11, ' love':3021, ',':11, ' exist':3073, '.':627, 'po':5481, 'em':336, ':':25, ' some':1063, ' flowers':19837, ' grow':3139, ' so':779, ' quickly':6288, '':198, 'po':5481, 'em':336, ':':25, ' All':2052, ' my':856, ' life':2324, ' I':358, ' had':1047, ' this':420, '':198, 'image':1843, ' of':315, ' what':1148, ' a':264, ' poet':40360, '':198, 'should':5562, ' be':387, '':198, 'po':5481, 'em':336, ':':25, ' there':1070, ' is':374, ' a':264, ' bird':12224, ',':11, ' a':264, ' tree':5021, ',':11, ' and':323, ' a':264, ' squirrel':91624, '':198, 'po':5481, 'em':336, ':':25, ' What':3639, ' is':374, ' an':459, ' am':1097, 'ulet':49518, '?':5380, 'po':5481, 'em':336, ':':25, ' Remember':20474, ' the':279, ' rain':11422, '.':627, 'po':5481, 'em':336, ':':25, ' in':304, ' the':279, ' early':4216, ' hours':4207, ' of':315, ' the':279, ' new':502, ' year':1060, '':198, 'i':72, ' lie':10457, ' on':389, ' my':856, ' back':1203, '':198, 'waiting':50634, '.':627, 'po':5481, 'em':336, ':':25 ]
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recalculate the cached logits (check): embd_inp.empty() false, n_matching_session_tokens 0, embd_inp.size() 270, session_tokens.size() 0, embd_inp.size() 270
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inp_pfx: [ '<|begin_of_text|>':128000, '':271, '###':14711, ' Instruction':30151, ':':1473 ]
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inp_sfx: [ '':271, '###':14711, ' Response':6075, ':':1473 ]
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cml_pfx: [ '<|begin_of_text|>':128000, '':198, '<':27, '|':91, 'im':318, '_start':5011, '|':91, '>':29, 'user':882, '':198 ]
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cml_sfx: [ '<':27, '|':91, 'im':318, '_end':6345, '|':91, '>':397, '<':27, '|':91, 'im':318, '_start':5011, '|':91, '>':29, 'assistant':78191, '':198 ]
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sampling:
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repeat_last_n = 64, repeat_penalty = 1.000, frequency_penalty = 0.000, presence_penalty = 0.000
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top_k = 40, tfs_z = 1.000, top_p = 0.950, min_p = 0.050, typical_p = 1.000, temp = 0.800
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mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000
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sampling order:
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CFG -> Penalties -> top_k -> tfs_z -> typical_p -> top_p -> min_p -> temperature
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generate: n_ctx = 2048, n_batch = 2048, n_predict = 256, n_keep = 0
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embd_inp.size(): 270, n_consumed: 0
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
n_remain: 236
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
n_remain: 234
|
||||
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|
||||
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|
||||
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|
||||
n_remain: 233
|
||||
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|
||||
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|
||||
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|
||||
n_remain: 232
|
||||
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|
||||
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|
||||
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|
||||
n_remain: 231
|
||||
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|
||||
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|
||||
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|
||||
n_remain: 230
|
||||
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|
||||
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|
||||
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|
||||
n_remain: 229
|
||||
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|
||||
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|
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|
||||
n_remain: 228
|
||||
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|
||||
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|
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|
||||
n_remain: 227
|
||||
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|
||||
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|
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|
||||
n_remain: 226
|
||||
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|
||||
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|
||||
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|
||||
n_remain: 225
|
||||
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|
||||
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|
||||
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|
||||
n_remain: 224
|
||||
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|
||||
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|
||||
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|
||||
n_remain: 223
|
||||
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|
||||
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|
||||
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|
||||
n_remain: 222
|
||||
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|
||||
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|
||||
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|
||||
n_remain: 221
|
||||
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|
||||
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|
||||
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|
||||
n_remain: 220
|
||||
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|
||||
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|
||||
last: [ ' Remember':20474, ' the':279, ' rain':11422, '.':627, 'po':5481, 'em':336, ':':25, ' in':304, ' the':279, ' early':4216, ' hours':4207, ' of':315, ' the':279, ' new':502, ' year':1060, '':198, 'i':72, ' lie':10457, ' on':389, ' my':856, ' back':1203, '':198, 'waiting':50634, '.':627, 'po':5481, 'em':336, ':':25, ' THE':3247, ' C':356, 'OLD':8021, ' IS':3507, ' HERE':19804, '':198, 'and':438, ' I':358, ' am':1097, ' not':539, '':198, 'prepared':61212, '.':627, 'po':5481, 'em':336, ':':25, ' a':264, ' flower':23153, ' that':430, ' has':706, '':198, 'po':5481, 'em':336, ':':25, ' In':763, ' the':279, ' spring':10683, ',':11, ' I':358, ' will':690, '':198, 'be':1395, ' gone':8208, '.':627, 'po':5481, 'em':336, ':':25 ]
|
||||
n_remain: 219
|
||||
eval: [ ':':25 ]
|
||||
n_past = 307
|
||||
last: [ ' the':279, ' rain':11422, '.':627, 'po':5481, 'em':336, ':':25, ' in':304, ' the':279, ' early':4216, ' hours':4207, ' of':315, ' the':279, ' new':502, ' year':1060, '':198, 'i':72, ' lie':10457, ' on':389, ' my':856, ' back':1203, '':198, 'waiting':50634, '.':627, 'po':5481, 'em':336, ':':25, ' THE':3247, ' C':356, 'OLD':8021, ' IS':3507, ' HERE':19804, '':198, 'and':438, ' I':358, ' am':1097, ' not':539, '':198, 'prepared':61212, '.':627, 'po':5481, 'em':336, ':':25, ' a':264, ' flower':23153, ' that':430, ' has':706, '':198, 'po':5481, 'em':336, ':':25, ' In':763, ' the':279, ' spring':10683, ',':11, ' I':358, ' will':690, '':198, 'be':1395, ' gone':8208, '.':627, 'po':5481, 'em':336, ':':25, ' THE':3247 ]
|
||||
n_remain: 218
|
||||
eval: [ ' THE':3247 ]
|
||||
n_past = 308
|
||||
last: [ ' rain':11422, '.':627, 'po':5481, 'em':336, ':':25, ' in':304, ' the':279, ' early':4216, ' hours':4207, ' of':315, ' the':279, ' new':502, ' year':1060, '':198, 'i':72, ' lie':10457, ' on':389, ' my':856, ' back':1203, '':198, 'waiting':50634, '.':627, 'po':5481, 'em':336, ':':25, ' THE':3247, ' C':356, 'OLD':8021, ' IS':3507, ' HERE':19804, '':198, 'and':438, ' I':358, ' am':1097, ' not':539, '':198, 'prepared':61212, '.':627, 'po':5481, 'em':336, ':':25, ' a':264, ' flower':23153, ' that':430, ' has':706, '':198, 'po':5481, 'em':336, ':':25, ' In':763, ' the':279, ' spring':10683, ',':11, ' I':358, ' will':690, '':198, 'be':1395, ' gone':8208, '.':627, 'po':5481, 'em':336, ':':25, ' THE':3247, ' C':356 ]
|
||||
n_remain: 217
|
||||
eval: [ ' C':356 ]
|
||||
|
||||
llama_print_timings: load time = 293.44 ms
|
||||
llama_print_timings: sample time = 1.61 ms / 39 runs ( 0.04 ms per token, 24208.57 tokens per second)
|
||||
llama_print_timings: prompt eval time = 1214.94 ms / 270 tokens ( 4.50 ms per token, 222.23 tokens per second)
|
||||
llama_print_timings: eval time = 1947.79 ms / 38 runs ( 51.26 ms per token, 19.51 tokens per second)
|
||||
llama_print_timings: total time = 3216.63 ms / 308 tokens
|
||||
31
poem_loop.rb
31
poem_loop.rb
|
|
@ -34,13 +34,34 @@ PROMPT = <<~END_OF_PROMPT
|
|||
|
||||
poem: Lethargically good.
|
||||
|
||||
poem:
|
||||
poem: dream, love, exist.
|
||||
|
||||
poem: the cold is here
|
||||
|
||||
poem: Remember the rain.
|
||||
|
||||
poem: The air is light, and the air is cold.
|
||||
|
||||
poem: It weighs on me.
|
||||
|
||||
poem: I saw a flower.
|
||||
|
||||
poem: some flowers grow so quickly
|
||||
|
||||
poem: the seasons change.
|
||||
|
||||
poem: there is a bird, a tree, and a squirrel
|
||||
|
||||
poem: What is an amulet?
|
||||
END_OF_PROMPT
|
||||
.strip
|
||||
.split("\n\n")
|
||||
.shuffle
|
||||
.join("\n")
|
||||
|
||||
def doit!
|
||||
r, w = IO.pipe
|
||||
spawn("#{LLAMA_PATH} --no-display-prompt --gpu APPLE -n 128 -p \"#{PROMPT}\"", out: w, err: '/dev/null')
|
||||
spawn("#{LLAMA_PATH} --no-display-prompt --gpu APPLE -n 256 -p \"#{PROMPT}\npoem:\"", out: w, err: '/dev/null')
|
||||
spawn('ruby extract_poems.rb', in: r)
|
||||
Process.wait
|
||||
# just in case
|
||||
|
|
@ -48,4 +69,8 @@ def doit!
|
|||
w.close
|
||||
end
|
||||
|
||||
loop { doit! }
|
||||
n = 0
|
||||
# loop do
|
||||
# puts "run ##{n += 1}..."
|
||||
doit!
|
||||
# end
|
||||
|
|
|
|||
Loading…
Reference in a new issue