Closed kamrancr7 closed 8 months ago
pseudotensor
commented
9 months ago ggml_metal_graph_compute: command buffer 3 failed with status 5
GGML_ASSERT: /private/var/folders/04/4cp_4dx92nzd02j3kmgjhhhm0000gn/T/pip-install-_sop_2s8/llama-cpp-python_5d55959272714b1697d8e57d22b5373b/vendor/llama.cpp/ggml-metal.m:2385: false
Fatal Python error: Aborted@Mathanraj-Sharma Can you check? Maybe need to update llama_cpp_python or something.
Mathanraj-Sharma
commented
8 months ago @kamrancr7 I checked with the latest main branch following instructions at https://github.com/h2oai/h2ogpt/blob/main/docs/README_MACOS.md
I did not see any error, please re-open it if you still have issues.
cc: @pseudotensor
~/Desktop/h2ogpt on main !1 ?6 ❯ python generate.py --base_model=TheBloke/zephyr-7B-beta-GGUF --prompt_type=zephyr --max_seq_len=4096 ✘ INT h2ogpt
soundfile, librosa, and wavio not installed, disabling STT
soundfile, librosa, and wavio not installed, disabling TTS
Using Model llama
Starting get_model: llama
llama_model_loader: loaded meta data with 21 key-value pairs and 291 tensors from llamacpp_path/zephyr-7b-beta.Q5_K_M.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 = huggingfaceh4_zephyr-7b-beta
llama_model_loader: - kv 2: llama.context_length u32 = 32768
llama_model_loader: - kv 3: llama.embedding_length u32 = 4096
llama_model_loader: - kv 4: llama.block_count u32 = 32
llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336
llama_model_loader: - kv 6: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 7: llama.attention.head_count u32 = 32
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 = 10000.000000
llama_model_loader: - kv 11: general.file_type u32 = 17
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 = 2
llama_model_loader: - kv 20: general.quantization_version u32 = 2
llama_model_loader: - type f32: 65 tensors
llama_model_loader: - type q5_K: 193 tensors
llama_model_loader: - type q6_K: 33 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 = 32768
llm_load_print_meta: n_embd = 4096
llm_load_print_meta: n_head = 32
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_layer = 32
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 = 4
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 = 14336
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
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 = 10000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_yarn_orig_ctx = 32768
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: model type = 7B
llm_load_print_meta: model ftype = Q5_K - Medium
llm_load_print_meta: model params = 7.24 B
llm_load_print_meta: model size = 4.78 GiB (5.67 BPW)
llm_load_print_meta: general.name = huggingfaceh4_zephyr-7b-beta
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 = 2 '</s>'
llm_load_print_meta: LF token = 13 '<0x0A>'
llm_load_tensors: ggml ctx size = 0.22 MiB
ggml_backend_metal_buffer_from_ptr: allocated buffer, size = 4807.08 MiB, ( 4807.14 / 10922.67)
llm_load_tensors: offloading 32 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 33/33 layers to GPU
llm_load_tensors: CPU buffer size = 85.94 MiB
llm_load_tensors: Metal buffer size = 4807.07 MiB
...................................................................................................
llama_new_context_with_model: n_ctx = 4096
llama_new_context_with_model: freq_base = 10000.0
llama_new_context_with_model: freq_scale = 1
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: default.metallib not found, loading from source
ggml_metal_init: GGML_METAL_PATH_RESOURCES = nil
ggml_metal_init: loading '/Users/mathanraj/miniconda3/envs/h2ogpt/lib/python3.10/site-packages/llama_cpp/ggml-metal.metal'
ggml_metal_init: GPU name: Apple M1
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 = 11453.25 MB
ggml_backend_metal_buffer_type_alloc_buffer: allocated buffer, size = 512.00 MiB, ( 5320.95 / 10922.67)
llama_kv_cache_init: Metal KV buffer size = 512.00 MiB
llama_new_context_with_model: KV self size = 512.00 MiB, K (f16): 256.00 MiB, V (f16): 256.00 MiB
llama_new_context_with_model: CPU input buffer size = 36.04 MiB
ggml_backend_metal_buffer_type_alloc_buffer: allocated buffer, size = 592.02 MiB, ( 5912.97 / 10922.67)
llama_new_context_with_model: Metal compute buffer size = 592.00 MiB
llama_new_context_with_model: CPU compute buffer size = 16.00 MiB
llama_new_context_with_model: graph splits (measure): 2
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 |
Model metadata: {'general.quantization_version': '2', 'tokenizer.ggml.padding_token_id': '2', 'tokenizer.ggml.unknown_token_id': '0', 'tokenizer.ggml.eos_token_id': '2', 'tokenizer.ggml.bos_token_id': '1', 'tokenizer.ggml.model': 'llama', 'llama.attention.head_count_kv': '8', 'llama.context_length': '32768', 'llama.attention.head_count': '32', 'llama.rope.freq_base': '10000.000000', 'llama.rope.dimension_count': '128', 'general.file_type': '17', 'llama.feed_forward_length': '14336', 'llama.embedding_length': '4096', 'llama.block_count': '32', 'general.architecture': 'llama', 'llama.attention.layer_norm_rms_epsilon': '0.000010', 'general.name': 'huggingfaceh4_zephyr-7b-beta'}
Model {'base_model': 'llama', 'base_model0': 'llama', 'tokenizer_base_model': '', 'lora_weights': '', 'inference_server': '', 'prompt_type': 'zephyr', 'prompt_dict': {'promptA': '<|system|>\nYou are an AI that follows instructions extremely well and as helpful as possible.</s>\n', 'promptB': '<|system|>\nYou are an AI that follows instructions extremely well and as helpful as possible.</s>\n', 'PreInstruct': '<|user|>\n', 'PreInput': None, 'PreResponse': '</s>\n<|assistant|>\n', 'terminate_response': ['<|assistant|>', '</s>'], 'chat_sep': '', 'chat_turn_sep': '</s>\n', 'humanstr': '<|user|>', 'botstr': '<|assistant|>', 'generates_leading_space': False, 'system_prompt': 'You are an AI that follows instructions extremely well and as helpful as possible.', 'can_handle_system_prompt': True}, 'visible_models': None, 'h2ogpt_key': None, 'load_8bit': False, 'load_4bit': False, 'low_bit_mode': 1, 'load_half': False, 'use_flash_attention_2': False, 'load_gptq': '', 'load_awq': '', 'load_exllama': False, 'use_safetensors': False, 'revision': None, 'use_gpu_id': False, 'gpu_id': None, 'compile_model': None, 'use_cache': None, 'llamacpp_dict': {'n_gpu_layers': 100, 'use_mlock': True, 'n_batch': 1024, 'n_gqa': 0, 'model_path_llama': 'https://huggingface.co/TheBloke/zephyr-7B-beta-GGUF/resolve/main/zephyr-7b-beta.Q5_K_M.gguf?download=true', 'model_name_gptj': '', 'model_name_gpt4all_llama': '', 'model_name_exllama_if_no_config': ''}, 'rope_scaling': {}, 'max_seq_len': 4096, 'max_output_seq_len': None, 'exllama_dict': {}, 'gptq_dict': {}, 'attention_sinks': False, 'sink_dict': {}, 'truncation_generation': False, 'hf_model_dict': {}}
Begin auto-detect HF cache text generation models
/Users/mathanraj/.cache/huggingface/modules/transformers_modules/mosaicml/mpt-7b-chat/1a1d410c70591fcc1a46486a254cd0e600e7b1b4/configuration_mpt.py:114: UserWarning: alibi or rope is turned on, setting `learned_pos_emb` to `False.`
warnings.warn(f'alibi or rope is turned on, setting `learned_pos_emb` to `False.`')
/Users/mathanraj/.cache/huggingface/modules/transformers_modules/mosaicml/mpt-7b-chat/1a1d410c70591fcc1a46486a254cd0e600e7b1b4/configuration_mpt.py:141: UserWarning: If not using a Prefix Language Model, we recommend setting "attn_impl" to "flash" instead of "triton".
warnings.warn(UserWarning('If not using a Prefix Language Model, we recommend setting "attn_impl" to "flash" instead of "triton".'))
End auto-detect HF cache text generation models
Begin auto-detect llama.cpp models
End auto-detect llama.cpp models
/Users/mathanraj/miniconda3/envs/h2ogpt/lib/python3.10/site-packages/gradio/components/dropdown.py:173: UserWarning: The value passed into gr.Dropdown() is not in the list of choices. Please update the list of choices to include: None or set allow_custom_value=True.
warnings.warn(
Running on local URL: http://0.0.0.0:7860
To create a public link, set `share=True` in `launch()`.
Started Gradio Server and/or GUI: server_name: localhost port: None
Use local URL: http://localhost:7860/
/Users/mathanraj/miniconda3/envs/h2ogpt/lib/python3.10/site-packages/pydantic/_internal/_fields.py:151: UserWarning: Field "model_name" has conflict with protected namespace "model_".
You may be able to resolve this warning by setting `model_config['protected_namespaces'] = ()`.
warnings.warn(
/Users/mathanraj/miniconda3/envs/h2ogpt/lib/python3.10/site-packages/pydantic/_internal/_fields.py:151: UserWarning: Field "model_names" has conflict with protected namespace "model_".
You may be able to resolve this warning by setting `model_config['protected_namespaces'] = ()`.
warnings.warn(
OpenAI API URL: http://0.0.0.0:5001
INFO:__name__:OpenAI API URL: http://0.0.0.0:5001
OpenAI API key: EMPTY
INFO:__name__:OpenAI API key: EMPTY
while executing the following command my mac M1 is crashing