{
    "model": "tiiuae/falcon-40b",
    "base_model": "",
    "revision": "main",
    "private": false,
    "precision": "bfloat16",
    "params": 40.0,
    "architectures": "FalconForCausalLM",
    "weight_type": "Original",
    "status": "FAILED",
    "submitted_time": "2024-02-05T23:13:31Z",
    "model_type": "🟢 : pretrained",
    "source": "script",
    "job_id": 87,
    "job_start_time": "2024-02-07T21-06-25.854633",
    "error_msg": "CUDA out of memory. Tried to allocate 20.00 MiB. GPU 1 has a total capacty of 79.35 GiB of which 16.19 MiB is free. Process 1605417 has 79.33 GiB memory in use. Of the allocated memory 78.37 GiB is allocated by PyTorch, and 457.70 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF",
    "traceback": "Traceback (most recent call last):\n  File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/evaluate_llms.py\", line 187, in wait_download_and_run_request\n    run_request(\n  File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/evaluate_llms.py\", line 64, in run_request\n    results = run_eval_on_model(\n              ^^^^^^^^^^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/run_eval.py\", line 55, in run_eval_on_model\n    result = evaluate(\n             ^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/llm_leaderboard_eval_bot/lm_eval_util.py\", line 145, in evaluate\n    results = evaluator.simple_evaluate(\n              ^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/utils.py\", line 415, in _wrapper\n    return fn(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/evaluator.py\", line 159, in simple_evaluate\n    results = evaluate(\n              ^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/utils.py\", line 415, in _wrapper\n    return fn(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/evaluator.py\", line 343, in evaluate\n    resps = getattr(lm, reqtype)(cloned_reqs)\n            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/models/huggingface.py\", line 1512, in generate_until\n    cont = self._model_generate(\n           ^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/repos/llm_leaderboard/lm-evaluation-harness-pt/lm_eval/models/huggingface.py\", line 1057, in _model_generate\n    return self.model.generate(\n           ^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/utils/_contextlib.py\", line 115, in decorate_context\n    return func(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/generation/utils.py\", line 1718, in generate\n    return self.greedy_search(\n           ^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/transformers/generation/utils.py\", line 2579, in greedy_search\n    outputs = self(\n              ^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1518, in _wrapped_call_impl\n    return self._call_impl(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1527, in _call_impl\n    return forward_call(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/.cache/huggingface/modules/transformers_modules/tiiuae/falcon-40b/4a70170c215b36a3cce4b4253f6d0612bb7d4146/modeling_falcon.py\", line 900, in forward\n    transformer_outputs = self.transformer(\n                          ^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1518, in _wrapped_call_impl\n    return self._call_impl(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1527, in _call_impl\n    return forward_call(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/.cache/huggingface/modules/transformers_modules/tiiuae/falcon-40b/4a70170c215b36a3cce4b4253f6d0612bb7d4146/modeling_falcon.py\", line 797, in forward\n    outputs = block(\n              ^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1518, in _wrapped_call_impl\n    return self._call_impl(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1527, in _call_impl\n    return forward_call(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/.cache/huggingface/modules/transformers_modules/tiiuae/falcon-40b/4a70170c215b36a3cce4b4253f6d0612bb7d4146/modeling_falcon.py\", line 453, in forward\n    attn_outputs = self.self_attention(\n                   ^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1518, in _wrapped_call_impl\n    return self._call_impl(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/miniconda3/envs/torch21/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1527, in _call_impl\n    return forward_call(*args, **kwargs)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/root/.cache/huggingface/modules/transformers_modules/tiiuae/falcon-40b/4a70170c215b36a3cce4b4253f6d0612bb7d4146/modeling_falcon.py\", line 315, in forward\n    value_layer = torch.cat((past_value, value_layer), dim=1)\n                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\ntorch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. GPU 1 has a total capacty of 79.35 GiB of which 16.19 MiB is free. Process 1605417 has 79.33 GiB memory in use. Of the allocated memory 78.37 GiB is allocated by PyTorch, and 457.70 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF\n"
}