llama-cpp-python not using GPU on google colab #1780
Comments
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Here's an example that does work on a Google Colab T4 instance: %pip install --quiet https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.90-cu124/llama_cpp_python-0.2.90-cp310-cp310-linux_x86_64.whl
from llama_cpp import Llama
llm = Llama.from_pretrained(
repo_id="bartowski/Meta-Llama-3.1-8B-Instruct-GGUF",
filename="*Q4_K_M.gguf",
n_ctx=8192,
n_gpu_layers=-1,
verbose=True
)
llm("Q: Name the planets in the solar system? A: ") |
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!pip install huggingface-hub fsspec==2023.6.0 from llama_cpp import Llama llm = Llama.from_pretrained( llm("Q: Name the planets in the solar system? A: ") Requirement already satisfied: huggingface-hub in /usr/local/lib/python3.10/dist-packages (0.24.7) llama_print_timings: load time = 20.02 ms |
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llm_load_tensors: offloading 24 repeating layers to GPU |
Prerequisites
Please answer the following questions for yourself before submitting an issue.
Expected Behavior
Expected to load my model on the T4 GPU on colab
CUDA VERSION - 12.2
INSTALL COMMAND - !pip install llama-cpp-python
--extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu122 --verbose
Current Behavior
Zero GPU Usage
llama_model_loader: loaded meta data with 33 key-value pairs and 291 tensors from /root/.cache/huggingface/hub/models--AnirudhJM24--Llama3-OpenBioLLM-8B-Q4_K_M-GGUF/snapshots/8f01788085a3ac57ddb617392855d6188514b974/llama3-openbiollm-8b-q4_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.type str = model
llama_model_loader: - kv 2: general.name str = Meta Llama 3 8B
llama_model_loader: - kv 3: general.organization str = Meta Llama
llama_model_loader: - kv 4: general.basename str = Meta-Llama-3
llama_model_loader: - kv 5: general.size_label str = 8B
llama_model_loader: - kv 6: general.license str = llama3
llama_model_loader: - kv 7: general.base_model.count u32 = 1
llama_model_loader: - kv 8: general.base_model.0.name str = Meta Llama 3 8B
llama_model_loader: - kv 9: general.base_model.0.organization str = Meta Llama
llama_model_loader: - kv 10: general.base_model.0.repo_url str = https://huggingface.co/meta-llama/Met...
llama_model_loader: - kv 11: general.tags arr[str,10] = ["llama-3", "llama", "Mixtral", "inst...
llama_model_loader: - kv 12: general.languages arr[str,1] = ["en"]
llama_model_loader: - kv 13: llama.block_count u32 = 32
llama_model_loader: - kv 14: llama.context_length u32 = 8192
llama_model_loader: - kv 15: llama.embedding_length u32 = 4096
llama_model_loader: - kv 16: llama.feed_forward_length u32 = 14336
llama_model_loader: - kv 17: llama.attention.head_count u32 = 32
llama_model_loader: - kv 18: llama.attention.head_count_kv u32 = 8
llama_model_loader: - kv 19: llama.rope.freq_base f32 = 500000.000000
llama_model_loader: - kv 20: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 21: general.file_type u32 = 15
llama_model_loader: - kv 22: llama.vocab_size u32 = 128256
llama_model_loader: - kv 23: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 24: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 25: tokenizer.ggml.pre str = smaug-bpe
llama_model_loader: - kv 26: tokenizer.ggml.tokens arr[str,128256] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 27: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 28: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv 29: tokenizer.ggml.bos_token_id u32 = 128000
llama_model_loader: - kv 30: tokenizer.ggml.eos_token_id u32 = 128001
llama_model_loader: - kv 31: tokenizer.ggml.padding_token_id u32 = 128001
llama_model_loader: - kv 32: general.quantization_version u32 = 2
llama_model_loader: - type f32: 65 tensors
llama_model_loader: - type q4_K: 193 tensors
llama_model_loader: - type q6_K: 33 tensors
llm_load_vocab: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
llm_load_vocab: special tokens cache size = 256
llm_load_vocab: token to piece cache size = 0.8000 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 128256
llm_load_print_meta: n_merges = 280147
llm_load_print_meta: vocab_only = 0
llm_load_print_meta: n_ctx_train = 8192
llm_load_print_meta: n_embd = 4096
llm_load_print_meta: n_layer = 32
llm_load_print_meta: n_head = 32
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_swa = 0
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: f_logit_scale = 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: causal attn = 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 = 500000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn = 8192
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: ssm_dt_b_c_rms = 0
llm_load_print_meta: model type = 8B
llm_load_print_meta: model ftype = Q4_K - Medium
llm_load_print_meta: model params = 8.03 B
llm_load_print_meta: model size = 4.58 GiB (4.89 BPW)
llm_load_print_meta: general.name = Meta Llama 3 8B
llm_load_print_meta: BOS token = 128000 '<|begin_of_text|>'
llm_load_print_meta: EOS token = 128001 '<|end_of_text|>'
llm_load_print_meta: PAD token = 128001 '<|end_of_text|>'
llm_load_print_meta: LF token = 128 'Ä'
llm_load_print_meta: EOT token = 128009 '<|eot_id|>'
llm_load_print_meta: EOG token = 128001 '<|end_of_text|>'
llm_load_print_meta: EOG token = 128009 '<|eot_id|>'
llm_load_print_meta: max token length = 256
llm_load_tensors: ggml ctx size = 0.14 MiB
llm_load_tensors: CPU buffer size = 4685.30 MiB
........................................................................................
llama_new_context_with_model: n_ctx = 512
llama_new_context_with_model: n_batch = 512
llama_new_context_with_model: n_ubatch = 512
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base = 500000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: CPU KV buffer size = 64.00 MiB
llama_new_context_with_model: KV self size = 64.00 MiB, K (f16): 32.00 MiB, V (f16): 32.00 MiB
llama_new_context_with_model: CPU output buffer size = 0.49 MiB
llama_new_context_with_model: CPU compute buffer size = 258.50 MiB
llama_new_context_with_model: graph nodes = 1030
llama_new_context_with_model: graph splits = 1
AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | RISCV_VECT = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 |
Model metadata: {'tokenizer.ggml.eos_token_id': '128001', 'general.quantization_version': '2', 'tokenizer.ggml.model': 'gpt2', 'llama.vocab_size': '128256', 'general.file_type': '15', 'llama.attention.layer_norm_rms_epsilon': '0.000010', 'llama.rope.freq_base': '500000.000000', 'tokenizer.ggml.bos_token_id': '128000', 'llama.attention.head_count': '32', 'llama.feed_forward_length': '14336', 'general.architecture': 'llama', 'llama.attention.head_count_kv': '8', 'llama.block_count': '32', 'tokenizer.ggml.padding_token_id': '128001', 'general.basename': 'Meta-Llama-3', 'llama.embedding_length': '4096', 'general.base_model.0.organization': 'Meta Llama', 'tokenizer.ggml.pre': 'smaug-bpe', 'llama.context_length': '8192', 'general.name': 'Meta Llama 3 8B', 'llama.rope.dimension_count': '128', 'general.base_model.0.name': 'Meta Llama 3 8B', 'general.organization': 'Meta Llama', 'general.type': 'model', 'general.size_label': '8B', 'general.base_model.0.repo_url': 'https://huggingface.co/meta-llama/Meta-Llama-3-8B', 'general.license': 'llama3', 'general.base_model.count': '1'}
Environment and Context
Google Colab
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