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bug-unconfirmedhigh severityUsed to report high severity bugs in llama.cpp (Malfunctioning hinder important workflow)Used to report high severity bugs in llama.cpp (Malfunctioning hinder important workflow)
Description
What happened?
common.cpp
's llama_chat_apply_template
says:
res
can be -1 (e.g. in the case that the model's Jinja template is not matched by any pattern in llama_chat_apply_template_internal
?). When cast to size_t
it becomes significantly bigger than buf.size()
which leads to buf.resize(-1)
. This is followed by a crash of llama-cli
on my machine.
llama-server
seems to fall back to chatml
if no pattern matches the model's Jinja template:
Perhaps the same needs to be done for llama-cli
, and perhaps common.cpp
's llama_chat_apply_template
should be more defensive when llama_chat_apply_template_internal
returns -1, rather than trying to resize buf
to -1
Name and Version
$ ./llama-cli --version
version: 3246 (ac146628)
built with cc (Debian 12.2.0-14) 12.2.0 for x86_64-linux-gnu
What operating system are you seeing the problem on?
Linux
Relevant log output
$ ./llama-cli -m /models/bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF/DeepSeek-Coder-V2-Lite-Instruct-Q6_K.gguf -c 8192
Log start
main: build = 3246 (ac146628)
main: built with cc (Debian 12.2.0-14) 12.2.0 for x86_64-linux-gnu
main: seed = 1719466734
llama_model_loader: loaded meta data with 42 key-value pairs and 377 tensors from /models/bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF/DeepSeek-Coder-V2-Lite-Instruct-Q6_K.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 = deepseek2
llama_model_loader: - kv 1: general.name str = DeepSeek-Coder-V2-Lite-Instruct
llama_model_loader: - kv 2: deepseek2.block_count u32 = 27
llama_model_loader: - kv 3: deepseek2.context_length u32 = 163840
llama_model_loader: - kv 4: deepseek2.embedding_length u32 = 2048
llama_model_loader: - kv 5: deepseek2.feed_forward_length u32 = 10944
llama_model_loader: - kv 6: deepseek2.attention.head_count u32 = 16
llama_model_loader: - kv 7: deepseek2.attention.head_count_kv u32 = 16
llama_model_loader: - kv 8: deepseek2.rope.freq_base f32 = 10000.000000
llama_model_loader: - kv 9: deepseek2.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 10: deepseek2.expert_used_count u32 = 6
llama_model_loader: - kv 11: general.file_type u32 = 18
llama_model_loader: - kv 12: deepseek2.leading_dense_block_count u32 = 1
llama_model_loader: - kv 13: deepseek2.vocab_size u32 = 102400
llama_model_loader: - kv 14: deepseek2.attention.kv_lora_rank u32 = 512
llama_model_loader: - kv 15: deepseek2.attention.key_length u32 = 192
llama_model_loader: - kv 16: deepseek2.attention.value_length u32 = 128
llama_model_loader: - kv 17: deepseek2.expert_feed_forward_length u32 = 1408
llama_model_loader: - kv 18: deepseek2.expert_count u32 = 64
llama_model_loader: - kv 19: deepseek2.expert_shared_count u32 = 2
llama_model_loader: - kv 20: deepseek2.expert_weights_scale f32 = 1.000000
llama_model_loader: - kv 21: deepseek2.rope.dimension_count u32 = 64
llama_model_loader: - kv 22: deepseek2.rope.scaling.type str = yarn
llama_model_loader: - kv 23: deepseek2.rope.scaling.factor f32 = 40.000000
llama_model_loader: - kv 24: deepseek2.rope.scaling.original_context_length u32 = 4096
llama_model_loader: - kv 25: deepseek2.rope.scaling.yarn_log_multiplier f32 = 0.070700
llama_model_loader: - kv 26: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 27: tokenizer.ggml.pre str = deepseek-llm
llama_model_loader: - kv 28: tokenizer.ggml.tokens arr[str,102400] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 29: tokenizer.ggml.token_type arr[i32,102400] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 30: tokenizer.ggml.merges arr[str,99757] = ["Ġ Ġ", "Ġ t", "Ġ a", "i n", "h e...
llama_model_loader: - kv 31: tokenizer.ggml.bos_token_id u32 = 100000
llama_model_loader: - kv 32: tokenizer.ggml.eos_token_id u32 = 100001
llama_model_loader: - kv 33: tokenizer.ggml.padding_token_id u32 = 100001
llama_model_loader: - kv 34: tokenizer.ggml.add_bos_token bool = true
llama_model_loader: - kv 35: tokenizer.ggml.add_eos_token bool = false
llama_model_loader: - kv 36: tokenizer.chat_template str = {% if not add_generation_prompt is de...
llama_model_loader: - kv 37: general.quantization_version u32 = 2
llama_model_loader: - kv 38: quantize.imatrix.file str = /models/DeepSeek-Coder-V2-Lite-Instru...
llama_model_loader: - kv 39: quantize.imatrix.dataset str = /training_data/calibration_datav3.txt
llama_model_loader: - kv 40: quantize.imatrix.entries_count i32 = 293
llama_model_loader: - kv 41: quantize.imatrix.chunks_count i32 = 139
llama_model_loader: - type f32: 108 tensors
llama_model_loader: - type q8_0: 27 tensors
llama_model_loader: - type q6_K: 242 tensors
llm_load_vocab: special tokens cache size = 2400
llm_load_vocab: token to piece cache size = 0.6661 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = deepseek2
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 102400
llm_load_print_meta: n_merges = 99757
llm_load_print_meta: n_ctx_train = 163840
llm_load_print_meta: n_embd = 2048
llm_load_print_meta: n_head = 16
llm_load_print_meta: n_head_kv = 16
llm_load_print_meta: n_layer = 27
llm_load_print_meta: n_rot = 64
llm_load_print_meta: n_embd_head_k = 192
llm_load_print_meta: n_embd_head_v = 128
llm_load_print_meta: n_gqa = 1
llm_load_print_meta: n_embd_k_gqa = 3072
llm_load_print_meta: n_embd_v_gqa = 2048
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 = 10944
llm_load_print_meta: n_expert = 64
llm_load_print_meta: n_expert_used = 6
llm_load_print_meta: causal attn = 1
llm_load_print_meta: pooling type = 0
llm_load_print_meta: rope type = 0
llm_load_print_meta: rope scaling = yarn
llm_load_print_meta: freq_base_train = 10000.0
llm_load_print_meta: freq_scale_train = 0.025
llm_load_print_meta: n_ctx_orig_yarn = 4096
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 = 16B
llm_load_print_meta: model ftype = Q6_K
llm_load_print_meta: model params = 15.71 B
llm_load_print_meta: model size = 13.10 GiB (7.16 BPW)
llm_load_print_meta: general.name = DeepSeek-Coder-V2-Lite-Instruct
llm_load_print_meta: BOS token = 100000 '<|begin▁of▁sentence|>'
llm_load_print_meta: EOS token = 100001 '<|end▁of▁sentence|>'
llm_load_print_meta: PAD token = 100001 '<|end▁of▁sentence|>'
llm_load_print_meta: LF token = 126 'Ä'
llm_load_print_meta: max token length = 256
llm_load_print_meta: n_layer_dense_lead = 1
llm_load_print_meta: n_lora_q = 0
llm_load_print_meta: n_lora_kv = 512
llm_load_print_meta: n_ff_exp = 1408
llm_load_print_meta: n_expert_shared = 2
llm_load_print_meta: expert_weights_scale = 1.0
llm_load_print_meta: rope_yarn_log_mul = 0.0707
llm_load_tensors: ggml ctx size = 0.16 MiB
llm_load_tensors: CPU buffer size = 13411.50 MiB
......................................................................................
llama_new_context_with_model: n_ctx = 8192
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 = 10000.0
llama_new_context_with_model: freq_scale = 0.025
llama_kv_cache_init: CPU KV buffer size = 2160.00 MiB
llama_new_context_with_model: KV self size = 2160.00 MiB, K (f16): 1296.00 MiB, V (f16): 864.00 MiB
llama_new_context_with_model: CPU output buffer size = 0.39 MiB
llama_new_context_with_model: CPU compute buffer size = 296.01 MiB
llama_new_context_with_model: graph nodes = 1924
llama_new_context_with_model: graph splits = 1
terminate called after throwing an instance of 'std::length_error'
what(): vector::_M_default_append
Aborted (core dumped)
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bug-unconfirmedhigh severityUsed to report high severity bugs in llama.cpp (Malfunctioning hinder important workflow)Used to report high severity bugs in llama.cpp (Malfunctioning hinder important workflow)