ggml_cuda_init: found 1 CUDA devices (Total VRAM: 7619 MiB): Device 0: Orin, compute capability 8.7, VMM: yes, VRAM: 7619 MiB build_info: b8849-747eb3686 system_info: n_threads = 6 (n_threads_batch = 6) / 6 | CUDA : ARCHS = 870 | USE_GRAPHS = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : NEON = 1 | ARM_FMA = 1 | FP16_VA = 1 | DOTPROD = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 | init: using 5 threads for HTTP server start: binding port with default address family main: loading model srv load_model: loading model '/home/yuvrajsingh/Bonsai-demo/models/ternary-gguf/8B/Ternary-Bonsai-8B-Q2_0.gguf' common_init_result: fitting params to device memory, for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on llama_params_fit_impl: projected to use 2438 MiB of device memory vs. 4876 MiB of free device memory llama_params_fit_impl: will leave 2438 >= 1024 MiB of free device memory, no changes needed llama_params_fit: successfully fit params to free device memory llama_params_fit: fitting params to free memory took 0.81 seconds llama_model_load_from_file_impl: using device CUDA0 (Orin) (0000:00:00.0) - 4884 MiB free llama_model_loader: loaded meta data with 35 key-value pairs and 399 tensors from /home/yuvrajsingh/Bonsai-demo/models/ternary-gguf/8B/Ternary-Bonsai-8B-Q2_0.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 = qwen3 llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.sampling.top_k i32 = 20 llama_model_loader: - kv 3: general.sampling.top_p f32 = 0.850000 llama_model_loader: - kv 4: general.sampling.min_p f32 = 0.000000 llama_model_loader: - kv 5: general.sampling.temp f32 = 0.500000 llama_model_loader: - kv 6: general.finetune str = unpacked llama_model_loader: - kv 7: general.basename str = Ternary-Bonsai llama_model_loader: - kv 8: general.size_label str = 8B llama_model_loader: - kv 9: general.license str = apache-2.0 llama_model_loader: - kv 10: general.tags arr[str,3] = ["prismml", "bonsai", "ternary"] llama_model_loader: - kv 11: qwen3.block_count u32 = 36 llama_model_loader: - kv 12: qwen3.context_length u32 = 65536 llama_model_loader: - kv 13: qwen3.embedding_length u32 = 4096 llama_model_loader: - kv 14: qwen3.feed_forward_length u32 = 12288 llama_model_loader: - kv 15: qwen3.attention.head_count u32 = 32 llama_model_loader: - kv 16: qwen3.attention.head_count_kv u32 = 8 llama_model_loader: - kv 17: qwen3.rope.scaling.type str = yarn llama_model_loader: - kv 18: qwen3.rope.scaling.factor f32 = 4.000000 llama_model_loader: - kv 19: qwen3.rope.scaling.original_context_length u32 = 16384 llama_model_loader: - kv 20: qwen3.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 21: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 22: qwen3.attention.key_length u32 = 128 llama_model_loader: - kv 23: qwen3.attention.value_length u32 = 128 llama_model_loader: - kv 24: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 25: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 26: tokenizer.ggml.tokens arr[str,151669] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 27: tokenizer.ggml.token_type arr[i32,151669] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 28: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 29: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 30: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 31: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 32: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 33: general.quantization_version u32 = 2 llama_model_loader: - kv 34: general.file_type u32 = 41 llama_model_loader: - type f32: 145 tensors llama_model_loader: - type q2_0: 254 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q2_0 print_info: file size = 2.03 GiB (2.13 BPW) load: 0 unused tokens load: control-looking token: 128247 '' was not control-type; this is probably a bug in the model. its type will be overridden load: printing all EOG tokens: load: - 128247 ('') load: - 151643 ('<|endoftext|>') load: - 151645 ('<|im_end|>') load: - 151662 ('<|fim_pad|>') load: - 151663 ('<|repo_name|>') load: - 151664 ('<|file_sep|>') load: special tokens cache size = 27 load: token to piece cache size = 0.9311 MB print_info: arch = qwen3 print_info: vocab_only = 0 print_info: no_alloc = 0 print_info: n_ctx_train = 65536 print_info: n_embd = 4096 print_info: n_embd_inp = 4096 print_info: n_layer = 36 print_info: n_head = 32 print_info: n_head_kv = 8 print_info: n_rot = 128 print_info: n_swa = 0 print_info: is_swa_any = 0 print_info: n_embd_head_k = 128 print_info: n_embd_head_v = 128 print_info: n_gqa = 4 print_info: n_embd_k_gqa = 1024 print_info: n_embd_v_gqa = 1024 print_info: f_norm_eps = 0.0e+00 print_info: f_norm_rms_eps = 1.0e-06 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 = 12288 print_info: n_expert = 0 print_info: n_expert_used = 0 print_info: n_expert_groups = 0 print_info: n_group_used = 0 print_info: causal attn = 1 print_info: pooling type = -1 print_info: rope type = 2 print_info: rope scaling = yarn print_info: freq_base_train = 1000000.0 print_info: freq_scale_train = 0.25 print_info: n_ctx_orig_yarn = 16384 print_info: rope_yarn_log_mul = 0.0000 print_info: rope_finetuned = unknown print_info: model type = 8B print_info: model params = 8.19 B print_info: general.name = n/a print_info: vocab type = BPE print_info: n_vocab = 151669 print_info: n_merges = 151387 print_info: BOS token = 11 ',' print_info: EOS token = 151645 '<|im_end|>' print_info: EOT token = 151645 '<|im_end|>' print_info: PAD token = 151643 '<|endoftext|>' print_info: LF token = 198 'Ċ' print_info: FIM PRE token = 151659 '<|fim_prefix|>' print_info: FIM SUF token = 151661 '<|fim_suffix|>' print_info: FIM MID token = 151660 '<|fim_middle|>' print_info: FIM PAD token = 151662 '<|fim_pad|>' print_info: FIM REP token = 151663 '<|repo_name|>' print_info: FIM SEP token = 151664 '<|file_sep|>' print_info: EOG token = 128247 '' print_info: EOG token = 151643 '<|endoftext|>' print_info: EOG token = 151645 '<|im_end|>' print_info: EOG token = 151662 '<|fim_pad|>' print_info: EOG token = 151663 '<|repo_name|>' print_info: EOG token = 151664 '<|file_sep|>' print_info: max token length = 256 load_tensors: loading model tensors, this can take a while... (mmap = true, direct_io = false) NvMapMemAllocInternalTagged: 1075072515 error 12 NvMapMemHandleAlloc: error 0 NvMapMemAllocInternalTagged: 1075072515 error 12 NvMapMemHandleAlloc: error 0 ggml_backend_cuda_buffer_type_alloc_buffer: allocating 1918.05 MiB on device 0: cudaMalloc failed: out of memory alloc_tensor_range: failed to allocate CUDA0 buffer of size 2011218304 llama_model_load: error loading model: unable to allocate CUDA0 buffer llama_model_load_from_file_impl: failed to load model common_init_from_params: failed to load model '/home/yuvrajsingh/Bonsai-demo/models/ternary-gguf/8B/Ternary-Bonsai-8B-Q2_0.gguf' srv load_model: failed to load model, '/home/yuvrajsingh/Bonsai-demo/models/ternary-gguf/8B/Ternary-Bonsai-8B-Q2_0.gguf' srv operator(): operator(): cleaning up before exit... main: exiting due to model loading error