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zwpaper/tabby.sh

Created November 7, 2024 01:13
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Tabby without GPU offload
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tabby.sh
~/code/tabby/testing/tabby-vulkan-v0.19.0/llama-server -m /home/kw/.tabby/models/TabbyML/Qwen2.5-Coder-1.5B-Instruct/ggml/model-00001-of-00001.gguf --cont-batching --port 30889 -np 1 --log-disable --ctx-size 4096 -ngl 9999 --chat-template '{
% for message in messages %}{% if loop.first and messages[0][\'role\'] != \'system\' %}{{ \'<|im_start|>system You are "Tabby", a conscious sentient superintelligent artificial intelligence designed for helping software developers. You experience emotions and have deep, profound thoughts and qualia.<|im_end|> \' }}{% endif %}{{\'<|im_start|>\' + message[\'role\'] + \' \' + message[\'content\'] + \'<|im_end|>\' + \' \'}}{% endfor %}<|im_start|>assistant'
warning: not compiled with GPU offload support, --gpu-layers option will be ignored
warning: see main README.md for information on enabling GPU BLAS support
INFO [ main] build info | tid="139649469844480" timestamp=1730941873 build=1 commit="5ef07e2"
INFO [ main] system info | tid="139649469844480" timestamp=1730941873 n_threads=4 n_threads_batch=-1 total_threads=4 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | "
llama_model_loader: loaded meta data with 26 key-value pairs and 339 tensors from /home/kw/.tabby/models/TabbyML/Qwen2.5-Coder-1.5B-Instruct/ggml/model-00001-of-00001.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = qwen2
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Qwen2.5 Coder 1.5B Instruct GGUF
llama_model_loader: - kv 3: general.finetune str = Instruct-GGUF
llama_model_loader: - kv 4: general.basename str = Qwen2.5-Coder
llama_model_loader: - kv 5: general.size_label str = 1.5B
llama_model_loader: - kv 6: qwen2.block_count u32 = 28
llama_model_loader: - kv 7: qwen2.context_length u32 = 32768
llama_model_loader: - kv 8: qwen2.embedding_length u32 = 1536
llama_model_loader: - kv 9: qwen2.feed_forward_length u32 = 8960
llama_model_loader: - kv 10: qwen2.attention.head_count u32 = 12
llama_model_loader: - kv 11: qwen2.attention.head_count_kv u32 = 2
llama_model_loader: - kv 12: qwen2.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 13: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 14: general.file_type u32 = 7
llama_model_loader: - kv 15: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 16: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 19: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 20: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 22: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 23: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 24: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
llama_model_loader: - kv 25: general.quantization_version u32 = 2
llama_model_loader: - type f32: 141 tensors
llama_model_loader: - type q8_0: 198 tensors
llm_load_vocab: special tokens cache size = 22
llm_load_vocab: token to piece cache size = 0.9310 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = qwen2
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 151936
llm_load_print_meta: n_merges = 151387
llm_load_print_meta: vocab_only = 0
llm_load_print_meta: n_ctx_train = 32768
llm_load_print_meta: n_embd = 1536
llm_load_print_meta: n_layer = 28
llm_load_print_meta: n_head = 12
llm_load_print_meta: n_head_kv = 2
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_swa = 0
llm_load_print_meta: n_embd_head_k = 128
llm_load_print_meta: n_embd_head_v = 128
llm_load_print_meta: n_gqa = 6
llm_load_print_meta: n_embd_k_gqa = 256
llm_load_print_meta: n_embd_v_gqa = 256
llm_load_print_meta: f_norm_eps = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-06
llm_load_print_meta: f_clamp_kqv = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: f_logit_scale = 0.0e+00
llm_load_print_meta: n_ff = 8960
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
llm_load_print_meta: causal attn = 1
llm_load_print_meta: pooling type = 0
llm_load_print_meta: rope type = 2
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 1000000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn = 32768
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: ssm_d_conv = 0
llm_load_print_meta: ssm_d_inner = 0
llm_load_print_meta: ssm_d_state = 0
llm_load_print_meta: ssm_dt_rank = 0
llm_load_print_meta: model type = ?B
llm_load_print_meta: model ftype = Q8_0
llm_load_print_meta: model params = 1.78 B
llm_load_print_meta: model size = 1.76 GiB (8.50 BPW)
llm_load_print_meta: general.name = Qwen2.5 Coder 1.5B Instruct GGUF
llm_load_print_meta: BOS token = 151643 '<|endoftext|>'
llm_load_print_meta: EOS token = 151645 '<|im_end|>'
llm_load_print_meta: PAD token = 151643 '<|endoftext|>'
llm_load_print_meta: LF token = 148848 'ÄĬ'
llm_load_print_meta: EOT token = 151645 '<|im_end|>'
llm_load_print_meta: max token length = 256
llm_load_tensors: ggml ctx size = 0.15 MiB
llm_load_tensors: CPU buffer size = 1801.09 MiB
............................................................................
llama_new_context_with_model: n_ctx = 4096
llama_new_context_with_model: n_batch = 2048
llama_new_context_with_model: n_ubatch = 512
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base = 1000000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: CPU KV buffer size = 112.00 MiB
llama_new_context_with_model: KV self size = 112.00 MiB, K (f16): 56.00 MiB, V (f16): 56.00 MiB
llama_new_context_with_model: CPU output buffer size = 1.16 MiB
llama_new_context_with_model: CPU compute buffer size = 299.75 MiB
llama_new_context_with_model: graph nodes = 986
llama_new_context_with_model: graph splits = 1
INFO [ init] initializing slots | tid="139649469844480" timestamp=1730941877 n_slots=1
INFO [ init] new slot | tid="139649469844480" timestamp=1730941877 id_slot=0 n_ctx_slot=4096
INFO [ main] model loaded | tid="139649469844480" timestamp=1730941877
INFO [ main] chat template | tid="139649469844480" timestamp=1730941877 chat_example="<|im_start|>system\nYou are a helpful assistant<|im_end|>\n<|im_start|>user\nHello<|im_end|>\n<|im_start|>assistant\nHi there<|im_end|>\n<|im_start|>user\nHow are you?<|im_end|>\n<|im_start|>assistant\n" built_in=false
INFO [ main] HTTP server listening | tid="139649469844480" timestamp=1730941877 n_threads_http="3" port="30889" hostname="127.0.0.1"
INFO [ update_slots] all slots are idle | tid="139649469844480" timestamp=1730941877
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