Closed
Description
Name and Version
$./llama-cli --version
load_backend: loaded CPU backend from /app/libggml-cpu-icelake.so
version: 5280 (27aa259)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
Operating systems
Linux
GGML backends
CPU
Hardware
8xRTX3090
Models
Meta Llama-3.2-1B-Instruct-16.gguf
Problem description & steps to reproduce
I tried to quantize F16.gguf llama-3.2-1b models into Q4_K_M. However, I encounter the segmentation fault error. Could you advise how to fix this error?
$:/app# ./llama-quantize models/Llama-3.2-1B-Instruct/Llama-3.2-1B-Instruct-F16.gguf models/Llama-3.2-1B-Instruct/gguf_quantized/ggml-model-Q4_K_M.gguf Q4_K_M```
### First Bad Commit
_No response_
### Relevant log output
```shell
main: build = 5280 (27aa2595)
main: built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
main: quantizing 'model/Llama-3.2-1B-Instruct/Llama-3.2-1B-Instruct-F16.gguf' to 'model/Llama-3.2-1B-Instruct/gguf_quantized/ggml-model-Q4_K_M.gguf' as Q4_K_M
llama_model_loader: loaded meta data with 31 key-value pairs and 147 tensors from model/Llama-3.2-1B-Instruct/Llama-3.2-1B-Instruct-F16.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 = llama
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Llama 3.2 1B Instruct
llama_model_loader: - kv 3: general.finetune str = Instruct
llama_model_loader: - kv 4: general.basename str = Llama-3.2
llama_model_loader: - kv 5: general.size_label str = 1B
llama_model_loader: - kv 6: general.license str = llama3.2
llama_model_loader: - kv 7: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv 8: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv 9: llama.block_count u32 = 16
llama_model_loader: - kv 10: llama.context_length u32 = 131072
llama_model_loader: - kv 11: llama.embedding_length u32 = 2048
llama_model_loader: - kv 12: llama.feed_forward_length u32 = 8192
llama_model_loader: - kv 13: llama.attention.head_count u32 = 32
llama_model_loader: - kv 14: llama.attention.head_count_kv u32 = 8
llama_model_loader: - kv 15: llama.rope.freq_base f32 = 500000.000000
llama_model_loader: - kv 16: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 17: llama.attention.key_length u32 = 64
llama_model_loader: - kv 18: llama.attention.value_length u32 = 64
llama_model_loader: - kv 19: general.file_type u32 = 1
llama_model_loader: - kv 20: llama.vocab_size u32 = 128256
llama_model_loader: - kv 21: llama.rope.dimension_count u32 = 64
llama_model_loader: - kv 22: general.quantization_version u32 = 2
llama_model_loader: - kv 23: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 24: tokenizer.ggml.pre str = llama-bpe
llama_model_loader: - kv 25: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 27: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv 28: tokenizer.ggml.bos_token_id u32 = 128000
llama_model_loader: - kv 29: tokenizer.ggml.eos_token_id u32 = 128009
llama_model_loader: - kv 30: tokenizer.chat_template str = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - type f32: 34 tensors
llama_model_loader: - type f16: 113 tensors
Segmentation fault (core dumped)