Cant finetune smollm2:360m #15532
Description
command: ./llama-finetune -p "bite me" -m ../SmolLM2-360M-Instruct-f16.gguf -o uzi
output:main: force disabling memory mapping because it would result in-read-only pointers to the weights
main: force changing k cache type to f32 due to a lack of f16 support for OUT_PROD
main: force changing v cache type to f32 due to a lack of f16 support for OUT_PROD
build: 6259 (710dfc4) with cc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 for x86_64-linux-gnu
llama_model_loader: loaded meta data with 33 key-value pairs and 290 tensors from ../SmolLM2-360M-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 = Smollm2 360M 8k Lc100K Mix1 Ep2
llama_model_loader: - kv 3: general.organization str = Loubnabnl
llama_model_loader: - kv 4: general.finetune str = 8k-lc100k-mix1-ep2
llama_model_loader: - kv 5: general.basename str = smollm2
llama_model_loader: - kv 6: general.size_label str = 360M
llama_model_loader: - kv 7: general.license str = apache-2.0
llama_model_loader: - kv 8: general.languages arr[str,1] = ["en"]
llama_model_loader: - kv 9: llama.block_count u32 = 32
llama_model_loader: - kv 10: llama.context_length u32 = 8192
llama_model_loader: - kv 11: llama.embedding_length u32 = 960
llama_model_loader: - kv 12: llama.feed_forward_length u32 = 2560
llama_model_loader: - kv 13: llama.attention.head_count u32 = 15
llama_model_loader: - kv 14: llama.attention.head_count_kv u32 = 5
llama_model_loader: - kv 15: llama.rope.freq_base f32 = 100000.000000
llama_model_loader: - kv 16: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 17: general.file_type u32 = 1
llama_model_loader: - kv 18: llama.vocab_size u32 = 49152
llama_model_loader: - kv 19: llama.rope.dimension_count u32 = 64
llama_model_loader: - kv 20: tokenizer.ggml.add_space_prefix bool = false
llama_model_loader: - kv 21: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 22: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 23: tokenizer.ggml.pre str = smollm
llama_model_loader: - kv 24: tokenizer.ggml.tokens arr[str,49152] = ["<|endoftext|>", "<|im_start|>", "<|...
llama_model_loader: - kv 25: tokenizer.ggml.token_type arr[i32,49152] = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
llama_model_loader: - kv 26: tokenizer.ggml.merges arr[str,48900] = ["Ġ t", "Ġ a", "i n", "h e", "Ġ Ġ...
llama_model_loader: - kv 27: tokenizer.ggml.bos_token_id u32 = 1
llama_model_loader: - kv 28: tokenizer.ggml.eos_token_id u32 = 2
llama_model_loader: - kv 29: tokenizer.ggml.unknown_token_id u32 = 0
llama_model_loader: - kv 30: tokenizer.ggml.padding_token_id u32 = 2
llama_model_loader: - kv 31: tokenizer.chat_template str = {% for message in messages %}{% if lo...
llama_model_loader: - kv 32: general.quantization_version u32 = 2
llama_model_loader: - type f32: 65 tensors
llama_model_loader: - type f16: 225 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = F16
print_info: file size = 690.24 MiB (16.00 BPW)
load: printing all EOG tokens:
load: - 0 ('<|endoftext|>')
load: - 2 ('<|im_end|>')
load: - 4 ('')
load: special tokens cache size = 17
load: token to piece cache size = 0.3170 MB
print_info: arch = llama
print_info: vocab_only = 0
print_info: n_ctx_train = 8192
print_info: n_embd = 960
print_info: n_layer = 32
print_info: n_head = 15
print_info: n_head_kv = 5
print_info: n_rot = 64
print_info: n_swa = 0
print_info: is_swa_any = 0
print_info: n_embd_head_k = 64
print_info: n_embd_head_v = 64
print_info: n_gqa = 3
print_info: n_embd_k_gqa = 320
print_info: n_embd_v_gqa = 320
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-05
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: f_attn_scale = 0.0e+00
print_info: n_ff = 2560
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: causal attn = 1
print_info: pooling type = 0
print_info: rope type = 0
print_info: rope scaling = linear
print_info: freq_base_train = 100000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 8192
print_info: rope_finetuned = unknown
print_info: model type = 3B
print_info: model params = 361.82 M
print_info: general.name = Smollm2 360M 8k Lc100K Mix1 Ep2
print_info: vocab type = BPE
print_info: n_vocab = 49152
print_info: n_merges = 48900
print_info: BOS token = 1 '<|im_start|>'
print_info: EOS token = 2 '<|im_end|>'
print_info: EOT token = 0 '<|endoftext|>'
print_info: UNK token = 0 '<|endoftext|>'
print_info: PAD token = 2 '<|im_end|>'
print_info: LF token = 198 'Ċ'
print_info: FIM REP token = 4 ''
print_info: EOG token = 0 '<|endoftext|>'
print_info: EOG token = 2 '<|im_end|>'
print_info: EOG token = 4 ''
print_info: max token length = 162
load_tensors: loading model tensors, this can take a while... (mmap = false)
load_tensors: CPU model buffer size = 690.24 MiB
........................................................................................
llama_context: constructing llama_context
llama_context: n_seq_max = 1
llama_context: n_ctx = 4096
llama_context: n_ctx_per_seq = 4096
llama_context: n_batch = 2048
llama_context: n_ubatch = 512
llama_context: causal_attn = 1
llama_context: flash_attn = 0
llama_context: kv_unified = false
llama_context: freq_base = 100000.0
llama_context: freq_scale = 1
llama_context: n_ctx_per_seq (4096) < n_ctx_train (8192) -- the full capacity of the model will not be utilized
llama_context: CPU output buffer size = 0.19 MiB
llama_kv_cache: CPU KV buffer size = 320.00 MiB
llama_kv_cache: size = 320.00 MiB ( 4096 cells, 32 layers, 1/1 seqs), K (f32): 160.00 MiB, V (f32): 160.00 MiB
llama_context: CPU compute buffer size = 136.76 MiB
llama_context: graph nodes = 1126
llama_context: graph splits = 1
common_init_from_params: added <|endoftext|> logit bias = -inf
common_init_from_params: added <|im_end|> logit bias = -inf
common_init_from_params: added logit bias = -inf
common_init_from_params: setting dry_penalty_last_n to ctx_size = 4096
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
system_info: n_threads = 2 (n_threads_batch = 2) / 4 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | F16C = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 |
ggml_aligned_malloc: insufficient memory (attempted to allocate 17592186044415.94 MB)
ggml_backend_cpu_buffer_type_alloc_buffer: failed to allocate buffer of size 18446744073709486080
alloc_tensor_range: failed to allocate CPU buffer of size 18446744073709486080
[New LWP 45805]
[New LWP 45804]
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warning: could not find '.gnu_debugaltlink' file for /lib/x86_64-linux-gnu/liblber.so.2
warning: could not find '.gnu_debugaltlink' file for /lib/x86_64-linux-gnu/libbrotlidec.so.1
warning: could not find '.gnu_debugaltlink' file for /lib/x86_64-linux-gnu/libbrotlicommon.so.1
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
0x000071af737107e3 in __GI___wait4 (pid=45806, stat_loc=0x0, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
warning: 30 ../sysdeps/unix/sysv/linux/wait4.c: No such file or directory
#0 0x000071af737107e3 in __GI___wait4 (pid=45806, stat_loc=0x0, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
30 in ../sysdeps/unix/sysv/linux/wait4.c
#1 0x000071af74082ef3 in ggml_print_backtrace () from /home/trent/uzi-gun/llama.cpp/build/bin/libggml-base.so
#2 0x000071af740946bf in ggml_uncaught_exception() () from /home/trent/uzi-gun/llama.cpp/build/bin/libggml-base.so
#3 0x000071af73abb0da in ?? () from /lib/x86_64-linux-gnu/libstdc++.so.6
#4 0x000071af73aa5a55 in std::terminate() () from /lib/x86_64-linux-gnu/libstdc++.so.6
#5 0x000071af73abb391 in __cxa_throw () from /lib/x86_64-linux-gnu/libstdc++.so.6
#6 0x000071af73aa5ac8 in ?? () from /lib/x86_64-linux-gnu/libstdc++.so.6
#7 0x000071af740a1249 in std::vector<long, std::allocator >::_M_default_append(unsigned long) () from /home/trent/uzi-gun/llama.cpp/build/bin/libggml-base.so
#8 0x000071af7409e677 in ggml_opt_dataset_init () from /home/trent/uzi-gun/llama.cpp/build/bin/libggml-base.so
#9 0x00006295478cbc29 in common_opt_dataset_init(llama_context*, std::vector<int, std::allocator > const&, long) ()
#10 0x00006295477d8cc7 in main ()
[Inferior 1 (process 45803) detached]
terminate called after throwing an instance of 'std::bad_alloc'
what(): std::bad_alloc
Aborted (core dumped)
runing on intel i5 ik its bad no gpu
Please help me. thanks