forked from ggml-org/llama.cpp
-
Notifications
You must be signed in to change notification settings - Fork 500
Closed
Labels
bugSomething isn't workingSomething isn't working
Description
Commit hash: edb05e7
Branch: concedo_experimental
With --gpulayers 80
:
% python koboldcpp.py --noblas --gpulayers 80 --model $LLM_MODEL_Q/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf
***
Welcome to KoboldCpp - Version 1.61
Warning: OpenBLAS library file not found. Non-BLAS library will be used.
Initializing dynamic library: koboldcpp_default.so
==========
Namespace(model='/Volumes/cuttingedge/large_language_models/models_ggml_converted/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf', model_param='/Volumes/cuttingedge/large_language_models/models_ggml_converted/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf', port=5001, port_param=5001, host='', launch=False, config=None, threads=4, usecublas=None, usevulkan=None, useclblast=None, noblas=True, gpulayers=80, tensor_split=None, contextsize=2048, ropeconfig=[0.0, 10000.0], blasbatchsize=512, blasthreads=4, lora=None, smartcontext=False, noshift=False, bantokens=None, forceversion=0, nommap=False, usemlock=False, noavx2=False, debugmode=0, skiplauncher=False, hordeconfig=None, onready='', benchmark=None, multiuser=0, remotetunnel=False, highpriority=False, foreground=False, preloadstory='', quiet=False, ssl=None, nocertify=False, sdconfig=None, mmproj='', password=None)
==========
Loading model: /Volumes/cuttingedge/large_language_models/models_ggml_converted/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf
[Threads: 4, BlasThreads: 4, SmartContext: False, ContextShift: True]
The reported GGUF Arch is: llama
---
Identified as GGUF model: (ver 6)
Attempting to Load...
---
Using automatic RoPE scaling. If the model has customized RoPE settings, they will be used directly instead!
System Info: AVX = 0 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 |
llama_model_loader: loaded meta data with 24 key-value pairs and 723 tensors from /Volumes/cuttingedge/large_language_models/models_ggml_converted/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf (version GGUF V3 (latest))
llm_load_vocab: special tokens definition check successful ( 259/32000 ).
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = SPM
llm_load_print_meta: n_vocab = 32000
llm_load_print_meta: n_merges = 0
llm_load_print_meta: n_ctx_train = 32764
llm_load_print_meta: n_embd = 8192
llm_load_print_meta: n_head = 64
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_layer = 80
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_embd_head_k = 128
llm_load_print_meta: n_embd_head_v = 128
llm_load_print_meta: n_gqa = 8
llm_load_print_meta: n_embd_k_gqa = 1024
llm_load_print_meta: n_embd_v_gqa = 1024
llm_load_print_meta: f_norm_eps = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-05
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: n_ff = 28672
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
llm_load_print_meta: causal attm = 1
llm_load_print_meta: pooling type = 0
llm_load_print_meta: rope type = 0
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_yarn_orig_ctx = 32764
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 = 70B
llm_load_print_meta: model ftype = Q4_1, some F16
llm_load_print_meta: model params = 68.98 B
llm_load_print_meta: model size = 23.71 GiB (2.95 BPW)
llm_load_print_meta: general.name = models
llm_load_print_meta: BOS token = 1 '<s>'
llm_load_print_meta: EOS token = 2 '</s>'
llm_load_print_meta: UNK token = 0 '<unk>'
llm_load_print_meta: PAD token = 0 '<unk>'
llm_load_print_meta: LF token = 13 '<0x0A>'
llm_load_tensors: ggml ctx size = 0.64 MiB
llm_load_tensors: offloading 80 repeating layers to GPU
llm_load_tensors: offloaded 80/81 layers to GPU
llm_load_tensors: CPU buffer size = 24282.14 MiB
llm_load_tensors: Metal buffer size = 24200.09 MiB
....................................................................................................
Automatic RoPE Scaling: Using model internal value.
llama_new_context_with_model: n_ctx = 2128
llama_new_context_with_model: freq_base = 1000000.0
llama_new_context_with_model: freq_scale = 1
llama_new_context_with_model: failed to initialize Metal backend
gpttype_load_model: error: failed to load model '/Volumes/cuttingedge/large_language_models/models_ggml_converted/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf'
Load Text Model OK: False
Could not load text model: /Volumes/cuttingedge/large_language_models/models_ggml_converted/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf
%
Without --gpulayers 80
:
% python koboldcpp.py --noblas --model $LLM_MODEL_Q/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf
***
Welcome to KoboldCpp - Version 1.61
Warning: OpenBLAS library file not found. Non-BLAS library will be used.
Initializing dynamic library: koboldcpp_default.so
==========
Namespace(model='/Volumes/cuttingedge/large_language_models/models_ggml_converted/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf', model_param='/Volumes/cuttingedge/large_language_models/models_ggml_converted/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf', port=5001, port_param=5001, host='', launch=False, config=None, threads=4, usecublas=None, usevulkan=None, useclblast=None, noblas=True, gpulayers=0, tensor_split=None, contextsize=2048, ropeconfig=[0.0, 10000.0], blasbatchsize=512, blasthreads=4, lora=None, smartcontext=False, noshift=False, bantokens=None, forceversion=0, nommap=False, usemlock=False, noavx2=False, debugmode=0, skiplauncher=False, hordeconfig=None, onready='', benchmark=None, multiuser=0, remotetunnel=False, highpriority=False, foreground=False, preloadstory='', quiet=False, ssl=None, nocertify=False, sdconfig=None, mmproj='', password=None)
==========
Loading model: /Volumes/cuttingedge/large_language_models/models_ggml_converted/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf
[Threads: 4, BlasThreads: 4, SmartContext: False, ContextShift: True]
The reported GGUF Arch is: llama
---
Identified as GGUF model: (ver 6)
Attempting to Load...
---
Using automatic RoPE scaling. If the model has customized RoPE settings, they will be used directly instead!
System Info: AVX = 0 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 |
llama_model_loader: loaded meta data with 24 key-value pairs and 723 tensors from /Volumes/cuttingedge/large_language_models/models_ggml_converted/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf (version GGUF V3 (latest))
llm_load_vocab: special tokens definition check successful ( 259/32000 ).
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = SPM
llm_load_print_meta: n_vocab = 32000
llm_load_print_meta: n_merges = 0
llm_load_print_meta: n_ctx_train = 32764
llm_load_print_meta: n_embd = 8192
llm_load_print_meta: n_head = 64
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_layer = 80
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_embd_head_k = 128
llm_load_print_meta: n_embd_head_v = 128
llm_load_print_meta: n_gqa = 8
llm_load_print_meta: n_embd_k_gqa = 1024
llm_load_print_meta: n_embd_v_gqa = 1024
llm_load_print_meta: f_norm_eps = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-05
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: n_ff = 28672
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
llm_load_print_meta: causal attm = 1
llm_load_print_meta: pooling type = 0
llm_load_print_meta: rope type = 0
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_yarn_orig_ctx = 32764
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 = 70B
llm_load_print_meta: model ftype = Q4_1, some F16
llm_load_print_meta: model params = 68.98 B
llm_load_print_meta: model size = 23.71 GiB (2.95 BPW)
llm_load_print_meta: general.name = models
llm_load_print_meta: BOS token = 1 '<s>'
llm_load_print_meta: EOS token = 2 '</s>'
llm_load_print_meta: UNK token = 0 '<unk>'
llm_load_print_meta: PAD token = 0 '<unk>'
llm_load_print_meta: LF token = 13 '<0x0A>'
llm_load_tensors: ggml ctx size = 0.32 MiB
llm_load_tensors: offloading 0 repeating layers to GPU
llm_load_tensors: offloaded 0/81 layers to GPU
llm_load_tensors: CPU buffer size = 24282.14 MiB
....................................................................................................
Automatic RoPE Scaling: Using model internal value.
llama_new_context_with_model: n_ctx = 2128
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 = 665.00 MiB
llama_new_context_with_model: KV self size = 665.00 MiB, K (f16): 332.50 MiB, V (f16): 332.50 MiB
llama_new_context_with_model: CPU input buffer size = 21.18 MiB
llama_new_context_with_model: CPU compute buffer size = 330.00 MiB
llama_new_context_with_model: graph splits (measure): 1
Load Text Model OK: True
Embedded Kobold Lite loaded.
Starting Kobold API on port 5001 at http://localhost:5001/api/
Starting OpenAI Compatible API on port 5001 at http://localhost:5001/v1/
======
Please connect to custom endpoint at http://localhost:5001
For comparison - server
with -ngl 999
from llama.cpp commit hash 306d34b:
% ./server -m /Volumes/cuttingedge/large_language_models/models_ggml_converted/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_K.gguf -ngl 999 -c 16384
{"build":2409,"commit":"306d34be","function":"main","level":"INFO","line":2732,"msg":"build info","tid":"0x1e27d5c40","timestamp":1710286276}
{"function":"main","level":"INFO","line":2739,"msg":"system info","n_threads":8,"n_threads_batch":-1,"system_info":"AVX = 0 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 | ","tid":"0x1e27d5c40","timestamp":1710286276,"total_threads":10}
llama_model_loader: loaded meta data with 24 key-value pairs and 723 tensors from /Volumes/cuttingedge/large_language_models/models_ggml_converted/maywell_kiqu-70b-GGUF/kiqu-70b.Q2_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 = llama
llama_model_loader: - kv 1: general.name str = models
llama_model_loader: - kv 2: llama.context_length u32 = 32764
llama_model_loader: - kv 3: llama.embedding_length u32 = 8192
llama_model_loader: - kv 4: llama.block_count u32 = 80
llama_model_loader: - kv 5: llama.feed_forward_length u32 = 28672
llama_model_loader: - kv 6: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 7: llama.attention.head_count u32 = 64
llama_model_loader: - kv 8: llama.attention.head_count_kv u32 = 8
llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 10: llama.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 11: general.file_type u32 = 10
llama_model_loader: - kv 12: tokenizer.ggml.model str = llama
llama_model_loader: - kv 13: tokenizer.ggml.tokens arr[str,32000] = ["<unk>", "<s>", "</s>", "<0x00>", "<...
llama_model_loader: - kv 14: tokenizer.ggml.scores arr[f32,32000] = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv 15: tokenizer.ggml.token_type arr[i32,32000] = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
llama_model_loader: - kv 16: tokenizer.ggml.bos_token_id u32 = 1
llama_model_loader: - kv 17: tokenizer.ggml.eos_token_id u32 = 2
llama_model_loader: - kv 18: tokenizer.ggml.unknown_token_id u32 = 0
llama_model_loader: - kv 19: tokenizer.ggml.padding_token_id u32 = 0
llama_model_loader: - kv 20: tokenizer.ggml.add_bos_token bool = true
llama_model_loader: - kv 21: tokenizer.ggml.add_eos_token bool = false
llama_model_loader: - kv 22: tokenizer.chat_template str = {{ bos_token }}{% for message in mess...
llama_model_loader: - kv 23: general.quantization_version u32 = 2
llama_model_loader: - type f32: 161 tensors
llama_model_loader: - type q2_K: 321 tensors
llama_model_loader: - type q3_K: 160 tensors
llama_model_loader: - type q5_K: 80 tensors
llama_model_loader: - type q6_K: 1 tensors
llm_load_vocab: special tokens definition check successful ( 259/32000 ).
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = SPM
llm_load_print_meta: n_vocab = 32000
llm_load_print_meta: n_merges = 0
llm_load_print_meta: n_ctx_train = 32764
llm_load_print_meta: n_embd = 8192
llm_load_print_meta: n_head = 64
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_layer = 80
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_embd_head_k = 128
llm_load_print_meta: n_embd_head_v = 128
llm_load_print_meta: n_gqa = 8
llm_load_print_meta: n_embd_k_gqa = 1024
llm_load_print_meta: n_embd_v_gqa = 1024
llm_load_print_meta: f_norm_eps = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-05
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: n_ff = 28672
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
llm_load_print_meta: causal attm = 1
llm_load_print_meta: pooling type = 0
llm_load_print_meta: rope type = 0
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_yarn_orig_ctx = 32764
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 = 70B
llm_load_print_meta: model ftype = Q2_K - Medium
llm_load_print_meta: model params = 68.98 B
llm_load_print_meta: model size = 23.71 GiB (2.95 BPW)
llm_load_print_meta: general.name = models
llm_load_print_meta: BOS token = 1 '<s>'
llm_load_print_meta: EOS token = 2 '</s>'
llm_load_print_meta: UNK token = 0 '<unk>'
llm_load_print_meta: PAD token = 0 '<unk>'
llm_load_print_meta: LF token = 13 '<0x0A>'
llm_load_tensors: ggml ctx size = 0.55 MiB
ggml_backend_metal_buffer_from_ptr: allocated buffer, size = 24200.12 MiB, (24200.19 / 49152.00)
llm_load_tensors: offloading 80 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 81/81 layers to GPU
llm_load_tensors: Metal buffer size = 24200.12 MiB
llm_load_tensors: CPU buffer size = 82.03 MiB
....................................................................................................
llama_new_context_with_model: n_ctx = 16384
llama_new_context_with_model: freq_base = 1000000.0
llama_new_context_with_model: freq_scale = 1
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1 Max
ggml_metal_init: picking default device: Apple M1 Max
ggml_metal_init: default.metallib not found, loading from source
ggml_metal_init: GGML_METAL_PATH_RESOURCES = nil
ggml_metal_init: loading '/Users/******/test/llama.cpp/ggml-metal.metal'
ggml_metal_init: GPU name: Apple M1 Max
ggml_metal_init: GPU family: MTLGPUFamilyApple7 (1007)
ggml_metal_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_init: GPU family: MTLGPUFamilyMetal3 (5001)
ggml_metal_init: simdgroup reduction support = true
ggml_metal_init: simdgroup matrix mul. support = true
ggml_metal_init: hasUnifiedMemory = true
ggml_metal_init: recommendedMaxWorkingSetSize = 51539.61 MB
ggml_backend_metal_buffer_type_alloc_buffer: allocated buffer, size = 5120.00 MiB, (29322.00 / 49152.00)
llama_kv_cache_init: Metal KV buffer size = 5120.00 MiB
llama_new_context_with_model: KV self size = 5120.00 MiB, K (f16): 2560.00 MiB, V (f16): 2560.00 MiB
llama_new_context_with_model: CPU input buffer size = 49.13 MiB
ggml_backend_metal_buffer_type_alloc_buffer: allocated buffer, size = 2144.02 MiB, (31466.02 / 49152.00)
llama_new_context_with_model: Metal compute buffer size = 2144.00 MiB
llama_new_context_with_model: CPU compute buffer size = 16.00 MiB
llama_new_context_with_model: graph splits (measure): 2
{"function":"init","level":"INFO","line":700,"msg":"initializing slots","n_slots":1,"tid":"0x1e27d5c40","timestamp":1710286281}
{"function":"init","id_slot":0,"level":"INFO","line":712,"msg":"new slot","n_ctx_slot":16384,"tid":"0x1e27d5c40","timestamp":1710286281}
{"function":"main","level":"INFO","line":2828,"msg":"model loaded","tid":"0x1e27d5c40","timestamp":1710286281}
{"built_in":true,"chat_example":"[INST] You are a helpful assistant\nHello [/INST]Hi there</s>[INST] How are you? [/INST]","function":"main","level":"INFO","line":2853,"msg":"chat template","tid":"0x1e27d5c40","timestamp":1710286281}
{"function":"main","hostname":"127.0.0.1","level":"INFO","line":3494,"msg":"HTTP server listening","n_threads_http":"9","port":"8080","tid":"0x1e27d5c40","timestamp":1710286281}
{"function":"update_slots","level":"INFO","line":1647,"msg":"all slots are idle","tid":"0x1e27d5c40","timestamp":1710286281}
Metadata
Metadata
Assignees
Labels
bugSomething isn't workingSomething isn't working