Upload 2025-12-22/runs/25858-20428481246/ci_results_run_models_gpu/model_results.json with huggingface_hub

2025-12-22/runs/25858-20428481246/ci_results_run_models_gpu/model_results.json

@@ -0,0 +1,1972 @@
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+        "captured_info": {}
+    },
+    "models_bamba": {
+        "failed": {
+            "PyTorch": {
+                "unclassified": 0,
+                "single": 3,
+                "multi": 3
+            },
+            "Tokenizers": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Pipelines": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Trainer": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "ONNX": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Auto": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Quantization": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Unclassified": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            }
+        },
+        "errors": 0,
+        "success": 211,
+        "skipped": 223,
+        "time_spent": [
+            75.8,
+            74.8
+        ],
+        "error": false,
+        "failures": {
+            "single": [
+                {
+                    "line": "tests/models/bamba/test_modeling_bamba.py::BambaModelTest::test_sdpa_can_compile_dynamic",
+                    "trace": "(line 1677)  torch._dynamo.exc.TorchRuntimeError: Dynamo failed to run FX node with fake tensors: call_function <built-in function scaled_dot_product_attention>(*(FakeTensor(..., device='cuda:0', size=(s47, 4, s87, 8), dtype=torch.float16), FakeTensor(..., device='cuda:0', size=(s47, 4, s87, 8), dtype=torch.float16), FakeTensor(..., device='cuda:0', size=(s47, 4, s87, 8), dtype=torch.float16)), **{'attn_mask': FakeTensor(..., device='cuda:0', size=(s84, 1, s34, s30), dtype=torch.float16), 'dropout_p': 0.0, 'scale': 0.353553390593274, 'is_causal': False}): got RuntimeError('expand: attempting to expand a dimension of length s30 -> s87!')"
+                },
+                {
+                    "line": "tests/models/bamba/test_modeling_bamba.py::BambaModelIntegrationTest::test_simple_batched_generate_with_padding",
+                    "trace": "(line 904)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 8.00 GiB. GPU 0 has a total capacity of 22.30 GiB of which 3.40 GiB is free. Process 26017 has 18.90 GiB memory in use. Of the allocated memory 18.54 GiB is allocated by PyTorch, and 4.28 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/bamba/test_modeling_bamba.py::BambaModelIntegrationTest::test_simple_generate",
+                    "trace": "(line 904)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU 0 has a total capacity of 22.30 GiB of which 3.25 GiB is free. Process 26017 has 19.04 GiB memory in use. Of the allocated memory 18.67 GiB is allocated by PyTorch, and 11.38 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/bamba/test_modeling_bamba.py::BambaModelTest::test_sdpa_can_compile_dynamic",
+                    "trace": "(line 1677)  torch._dynamo.exc.TorchRuntimeError: Dynamo failed to run FX node with fake tensors: call_function <built-in function scaled_dot_product_attention>(*(FakeTensor(..., device='cuda:0', size=(s47, 4, s87, 8), dtype=torch.float16), FakeTensor(..., device='cuda:0', size=(s47, 4, s87, 8), dtype=torch.float16), FakeTensor(..., device='cuda:0', size=(s47, 4, s87, 8), dtype=torch.float16)), **{'attn_mask': FakeTensor(..., device='cuda:0', size=(s84, 1, s34, s30), dtype=torch.float16), 'dropout_p': 0.0, 'scale': 0.353553390593274, 'is_causal': False}): got RuntimeError('expand: attempting to expand a dimension of length s30 -> s87!')"
+                },
+                {
+                    "line": "tests/models/bamba/test_modeling_bamba.py::BambaModelIntegrationTest::test_simple_batched_generate_with_padding",
+                    "trace": "(line 904)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 8.00 GiB. GPU 0 has a total capacity of 22.30 GiB of which 3.27 GiB is free. Process 25692 has 19.03 GiB memory in use. Of the allocated memory 18.54 GiB is allocated by PyTorch, and 12.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/bamba/test_modeling_bamba.py::BambaModelIntegrationTest::test_simple_generate",
+                    "trace": "(line 904)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU 0 has a total capacity of 22.30 GiB of which 3.12 GiB is free. Process 25692 has 19.17 GiB memory in use. Of the allocated memory 18.68 GiB is allocated by PyTorch, and 19.25 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                }
+            ]
+        },
+        "job_link": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087498",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087500"
+        },
+        "captured_info": {}
+    },
+    "models_bark": {
+        "failed": {
+            "PyTorch": {
+                "unclassified": 0,
+                "single": 1,
+                "multi": 1
+            },
+            "Tokenizers": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Pipelines": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Trainer": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "ONNX": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Auto": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Quantization": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Unclassified": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            }
+        },
+        "errors": 0,
+        "success": 410,
+        "skipped": 480,
+        "time_spent": [
+            793.41,
+            748.43
+        ],
+        "error": false,
+        "failures": {
+            "single": [
+                {
+                    "line": "tests/models/bark/test_modeling_bark.py::BarkModelIntegrationTests::test_generate_end_to_end_with_offload",
+                    "trace": "(line 2542)  RuntimeError: Expected all tensors to be on the same device, but got index is on cuda:0, different from other tensors on cpu (when checking argument in method wrapper_CUDA__index_select)"
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/bark/test_modeling_bark.py::BarkModelIntegrationTests::test_generate_end_to_end_with_offload",
+                    "trace": "(line 2542)  RuntimeError: Expected all tensors to be on the same device, but got index is on cuda:0, different from other tensors on cpu (when checking argument in method wrapper_CUDA__index_select)"
+                }
+            ]
+        },
+        "job_link": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087556",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087478"
+        },
+        "captured_info": {}
+    },
+    "models_bart": {
+        "failed": {
+            "PyTorch": {
+                "unclassified": 0,
+                "single": 1,
+                "multi": 1
+            },
+            "Tokenizers": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Pipelines": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Trainer": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "ONNX": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Auto": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Quantization": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Unclassified": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            }
+        },
+        "errors": 0,
+        "success": 484,
+        "skipped": 314,
+        "time_spent": [
+            212.49,
+            229.82
+        ],
+        "error": false,
+        "failures": {
+            "single": [
+                {
+                    "line": "tests/models/bart/test_modeling_bart.py::BartModelIntegrationTests::test_inference_no_head",
+                    "trace": "(line 907)  AssertionError: The values for attribute 'dtype' do not match: torch.float16 != torch.float32."
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/bart/test_modeling_bart.py::BartModelIntegrationTests::test_inference_no_head",
+                    "trace": "(line 907)  AssertionError: The values for attribute 'dtype' do not match: torch.float16 != torch.float32."
+                }
+            ]
+        },
+        "job_link": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087548",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087503"
+        },
+        "captured_info": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087548#step:16:1",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087503#step:16:1"
+        }
+    },
+    "models_bert": {
+        "failed": {
+            "PyTorch": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Tokenizers": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Pipelines": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Trainer": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "ONNX": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Auto": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Quantization": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Unclassified": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            }
+        },
+        "errors": 0,
+        "success": 355,
+        "skipped": 211,
+        "time_spent": [
+            207.12,
+            219.81
+        ],
+        "error": false,
+        "failures": {},
+        "job_link": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087571",
+            "single": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087419"
+        },
+        "captured_info": {}
+    },
+    "models_bert_generation": {
+        "failed": {
+            "PyTorch": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Tokenizers": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Pipelines": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Trainer": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "ONNX": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Auto": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Quantization": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Unclassified": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            }
+        },
+        "errors": 0,
+        "success": 347,
+        "skipped": 219,
+        "time_spent": [
+            104.08,
+            78.95
+        ],
+        "error": false,
+        "failures": {},
+        "job_link": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087433",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087496"
+        },
+        "captured_info": {}
+    },
+    "models_big_bird": {
+        "failed": {
+            "PyTorch": {
+                "unclassified": 0,
+                "single": 1,
+                "multi": 1
+            },
+            "Tokenizers": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Pipelines": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Trainer": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "ONNX": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Auto": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Quantization": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Unclassified": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            }
+        },
+        "errors": 0,
+        "success": 242,
+        "skipped": 246,
+        "time_spent": [
+            108.01,
+            123.79
+        ],
+        "error": false,
+        "failures": {
+            "multi": [
+                {
+                    "line": "tests/models/big_bird/test_modeling_big_bird.py::BigBirdModelIntegrationTest::test_fill_mask",
+                    "trace": "(line 911)  AssertionError: '' != 'happiness'"
+                }
+            ],
+            "single": [
+                {
+                    "line": "tests/models/big_bird/test_modeling_big_bird.py::BigBirdModelIntegrationTest::test_fill_mask",
+                    "trace": "(line 911)  AssertionError: '' != 'happiness'"
+                }
+            ]
+        },
+        "job_link": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087506",
+            "single": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087416"
+        },
+        "captured_info": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087506#step:16:1",
+            "single": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087416#step:16:1"
+        }
+    },
+    "models_gemma": {
+        "failed": {
+            "PyTorch": {
+                "unclassified": 0,
+                "single": 3,
+                "multi": 3
+            },
+            "Tokenizers": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Pipelines": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Trainer": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "ONNX": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Auto": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Quantization": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Unclassified": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            }
+        },
+        "errors": 0,
+        "success": 383,
+        "skipped": 197,
+        "time_spent": [
+            957.86,
+            946.82
+        ],
+        "error": false,
+        "failures": {
+            "single": [
+                {
+                    "line": "tests/models/gemma/test_modeling_gemma.py::GemmaIntegrationTest::test_export_static_cache",
+                    "trace": "(line 436)  AssertionError: Lists differ: ['Hel[87 chars] in the 1990s. I have been looking on the internet and I have'] != ['Hel[87 chars] in the 1990s. I have looked on the internet and I have found']"
+                },
+                {
+                    "line": "tests/models/gemma/test_modeling_gemma.py::GemmaIntegrationTest::test_model_7b_4bit",
+                    "trace": "(line 329)  AssertionError: Lists differ: ['Hel[42 chars]I am using a pic16f877a. I', 'Hi today I am go[68 chars]est'] != ['Hel[42 chars]I am trying to make a program that will take a[110 chars]!:)']"
+                },
+                {
+                    "line": "tests/models/gemma/test_modeling_gemma.py::GemmaIntegrationTest::test_model_7b_fp16_static_cache",
+                    "trace": "(line 299)  AssertionError: Lists differ: ['Hel[27 chars]a 1999 4.0L 4x4. I', 'Hi today I am going to s[51 chars] 3D'] != ['Hel[27 chars]a 1995 3000gt SL. I have a', 'Hi today I am go[59 chars] 3D']"
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/gemma/test_modeling_gemma.py::GemmaIntegrationTest::test_export_static_cache",
+                    "trace": "(line 436)  AssertionError: Lists differ: ['Hel[87 chars] in the 1990s. I have been looking on the internet and I have'] != ['Hel[87 chars] in the 1990s. I have looked on the internet and I have found']"
+                },
+                {
+                    "line": "tests/models/gemma/test_modeling_gemma.py::GemmaIntegrationTest::test_model_7b_4bit",
+                    "trace": "(line 329)  AssertionError: Lists differ: ['Hel[42 chars]I am using a pic16f877a. I', 'Hi today I am go[68 chars]est'] != ['Hel[42 chars]I am trying to make a program that will take a[110 chars]!:)']"
+                },
+                {
+                    "line": "tests/models/gemma/test_modeling_gemma.py::GemmaIntegrationTest::test_model_7b_fp16_static_cache",
+                    "trace": "(line 299)  AssertionError: Lists differ: ['Hel[27 chars]a 1999 4.0L 4x4. I', 'Hi today I am going to s[51 chars] 3D'] != ['Hel[27 chars]a 1995 3000gt SL. I have a', 'Hi today I am go[59 chars] 3D']"
+                }
+            ]
+        },
+        "job_link": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087423",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087559"
+        },
+        "captured_info": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087423#step:16:1",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20428481246/job/58694087559#step:16:1"
+        }
+    },
+    "models_gemma2": {
+        "failed": {
+            "PyTorch": {
+                "unclassified": 0,
+                "single": 4,
+                "multi": 4
+            },
+            "Tokenizers": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Pipelines": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Trainer": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "ONNX": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Auto": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Quantization": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Unclassified": {
+                "unclassified": 0,
+                "single": 1,
+                "multi": 1
+            }
+        },
+        "errors": 0,
+        "success": 272,
+        "skipped": 206,
+        "time_spent": [
+            585.94,
+            456.96
+        ],
+        "error": false,
+        "failures": {
+            "single": [
+                {
+                    "line": "[100%]",
+                    "trace": "(line 2774)  Failed: (subprocess) torch.AcceleratorError: CUDA error: an illegal memory access was encountered"
+                },
+                {
+                    "line": "tests/models/gemma2/test_modeling_gemma2.py::Gemma2IntegrationTest::test_model_2b_pipeline_bf16_flex_attention",
+                    "trace": "(line 62)  torch.AcceleratorError: CUDA error: an illegal memory access was encountered"
+                },
+                {
+                    "line": "tests/models/gemma2/test_modeling_gemma2.py::Gemma2IntegrationTest::test_model_9b_bf16_flex_attention",
+                    "trace": "(line 224)  torch.AcceleratorError: CUDA error: an illegal memory access was encountered"
+                },
+                {
+                    "line": "tests/models/gemma2/test_modeling_gemma2.py::Gemma2IntegrationTest::test_model_9b_fp16",
+                    "trace": "(line 224)  torch.AcceleratorError: CUDA error: an illegal memory access was encountered"
+                },
+                {
+                    "line": "tests/models/gemma2/test_modeling_gemma2.py::Gemma2IntegrationTest::test_model_9b_pipeline_bf16",
+                    "trace": "Cannot retrieve error message."
+                }
+            ],
+            "multi": [
+                {
+                    "line": "[100%]",
+                    "trace": "(line 2774)  Failed: (subprocess) torch.AcceleratorError: CUDA error: an illegal memory access was encountered"
+                },
+                {
+                    "line": "tests/models/gemma2/test_modeling_gemma2.py::Gemma2IntegrationTest::test_model_2b_pipeline_bf16_flex_attention",
+                    "trace": "(line 244)  RuntimeError: CUDA driver error: an illegal memory access was encountered"
+                },
+                {
+                    "line": "tests/models/gemma2/test_modeling_gemma2.py::Gemma2IntegrationTest::test_model_9b_bf16_flex_attention",
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+                },
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+                    "trace": "(line 224)  torch.AcceleratorError: CUDA error: an illegal memory access was encountered"
+                },
+                {
+                    "line": "tests/models/gemma2/test_modeling_gemma2.py::Gemma2IntegrationTest::test_model_9b_pipeline_bf16",
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+                },
+                {
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+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                },
+                {
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+                },
+                {
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+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                },
+                {
+                    "line": "tests/models/llama/test_tokenization_llama.py::LlamaTokenizationTest::test_truncation_side_in_kwargs",
+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                }
+            ],
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+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                },
+                {
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+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                },
+                {
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+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                },
+                {
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+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                },
+                {
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+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                }
+            ]
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+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_batched_generation",
+                    "trace": "(line 562)  AssertionError: Lists differ: [\"\\n\\nUSER: What's the difference of two imag[339 chars]ama'] != [\"\\n \\nUSER: What's the difference of two ima[362 chars]the']"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_generation_no_images",
+                    "trace": "(line 693)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 20.69 MiB is free. Process 76530 has 22.28 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 25.34 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_pixtral",
+                    "trace": "(line 543)  RuntimeError: Input type (torch.FloatTensor) and weight type (CPUBFloat16Type) should be the same or input should be a MKLDNN tensor and weight is a dense tensor"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_pixtral_4bit",
+                    "trace": "(line 693)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 50.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 44.69 MiB is free. Process 76530 has 22.25 GiB memory in use. Of the allocated memory 21.83 GiB is allocated by PyTorch, and 44.99 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_pixtral_batched",
+                    "trace": "(line 693)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 140.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 32.69 MiB is free. Process 76530 has 22.26 GiB memory in use. Of the allocated memory 21.86 GiB is allocated by PyTorch, and 18.76 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_small_model_integration_test",
+                    "trace": "(line 134)  RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::BFloat16 != float"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch",
+                    "trace": "(line 134)  RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::BFloat16 != float"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_small_model_integration_test_llama_batched",
+                    "trace": "(line 404)  AssertionError: Lists differ: ['USER: \\nWhat are the things I should be cautiou[269 chars] on'] != ['USER:  \\nWhat are the things I should be cautio[271 chars] on']"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_small_model_integration_test_llama_batched_regression",
+                    "trace": "(line 507)  AssertionError: Lists differ: ['USER: \\nWhat are the things I should be cautiou[280 chars]ed.'] != ['USER:  \\nWhat are the things I should be cautio[283 chars]ed.']"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_small_model_integration_test_llama_single",
+                    "trace": "(line 353)  AssertionError: 'USER: \\nWhat are the things I should be cautiou[748 chars]ies.' != 'USER:  \\nWhat are the things I should be cautio[749 chars]ies.'"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_tokenizer_integration",
+                    "trace": "(line 579)  AssertionError: Lists differ: ['<|im_start|>', '▁system', '\\n', '▁Answer', '▁the', '▁ques[176 chars]'\\n'] != ['<|im_start|>', 'system', '\\n', 'Answer', '▁the', '▁questi[175 chars]'\\n']"
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_batched_generation",
+                    "trace": "(line 562)  AssertionError: Lists differ: [\"\\n\\nUSER: What's the difference of two imag[339 chars]ama'] != [\"\\n \\nUSER: What's the difference of two ima[362 chars]the']"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_pixtral",
+                    "trace": "(line 543)  RuntimeError: Input type (torch.FloatTensor) and weight type (CPUBFloat16Type) should be the same or input should be a MKLDNN tensor and weight is a dense tensor"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_pixtral_4bit",
+                    "trace": "(line 693)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 40.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 12.69 MiB is free. Process 127830 has 22.28 GiB memory in use. Of the allocated memory 21.77 GiB is allocated by PyTorch, and 8.52 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_pixtral_batched",
+                    "trace": "(line 693)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 140.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 126.69 MiB is free. Process 127830 has 22.17 GiB memory in use. Of the allocated memory 21.65 GiB is allocated by PyTorch, and 27.35 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_small_model_integration_test",
+                    "trace": "(line 134)  RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::BFloat16 != float"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch",
+                    "trace": "(line 134)  RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::BFloat16 != float"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_small_model_integration_test_llama_batched",
+                    "trace": "(line 404)  AssertionError: Lists differ: ['USER: \\nWhat are the things I should be cautiou[269 chars] on'] != ['USER:  \\nWhat are the things I should be cautio[271 chars] on']"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_small_model_integration_test_llama_batched_regression",
+                    "trace": "(line 507)  AssertionError: Lists differ: ['USER: \\nWhat are the things I should be cautiou[280 chars]ed.'] != ['USER:  \\nWhat are the things I should be cautio[283 chars]ed.']"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_small_model_integration_test_llama_single",
+                    "trace": "(line 353)  AssertionError: 'USER: \\nWhat are the things I should be cautiou[748 chars]ies.' != 'USER:  \\nWhat are the things I should be cautio[749 chars]ies.'"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_tokenizer_integration",
+                    "trace": "(line 579)  AssertionError: Lists differ: ['<|im_start|>', '▁system', '\\n', '▁Answer', '▁the', '▁ques[176 chars]'\\n'] != ['<|im_start|>', 'system', '\\n', 'Answer', '▁the', '▁questi[175 chars]'\\n']"
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+                    "line": "tests/models/llava_next/test_modeling_llava_next.py::LlavaNextForConditionalGenerationIntegrationTest::test_small_model_integration_test_unk_token",
+                    "trace": "(line 424)  AssertionError: '[INS[24 chars]his  image? [/INST] The image appears to be a [185 chars]hart' != '[INS[24 chars]his   image? [/INST] The image appears to be a[186 chars]hart'"
+                }
+            ],
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+                {
+                    "line": "tests/models/llava_next/test_modeling_llava_next.py::LlavaNextForConditionalGenerationIntegrationTest::test_small_model_integration_test_unk_token",
+                    "trace": "(line 424)  AssertionError: '[INS[24 chars]his  image? [/INST] The image appears to be a [185 chars]hart' != '[INS[24 chars]his   image? [/INST] The image appears to be a[186 chars]hart'"
+                }
+            ]
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