Upload 2026-01-12/runs/26599-20926567527/ci_results_run_models_gpu/model_results.json with huggingface_hub

2026-01-12/runs/26599-20926567527/ci_results_run_models_gpu/model_results.json

@@ -0,0 +1,2031 @@
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+                "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": 213,
+        "skipped": 229,
+        "time_spent": [
+            78.57,
+            78.8
+        ],
+        "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.bfloat16), FakeTensor(..., device='cuda:0', size=(s47, 4, s87, 8), dtype=torch.bfloat16), FakeTensor(..., device='cuda:0', size=(s47, 4, s87, 8), dtype=torch.bfloat16)), **{'attn_mask': FakeTensor(..., device='cuda:0', size=(s84, 1, s34, s30), dtype=torch.bfloat16), '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 901)  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 17404 has 18.90 GiB memory in use. Of the allocated memory 18.54 GiB is allocated by PyTorch, and 4.01 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 901)  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 17404 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.bfloat16), FakeTensor(..., device='cuda:0', size=(s47, 4, s87, 8), dtype=torch.bfloat16), FakeTensor(..., device='cuda:0', size=(s47, 4, s87, 8), dtype=torch.bfloat16)), **{'attn_mask': FakeTensor(..., device='cuda:0', size=(s84, 1, s34, s30), dtype=torch.bfloat16), '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 901)  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 31362 has 19.03 GiB memory in use. Of the allocated memory 18.55 GiB is allocated by PyTorch, and 13.88 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 901)  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 31362 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/20926567527/job/60126219074",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219148"
+        },
+        "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": 416,
+        "skipped": 498,
+        "time_spent": [
+            739.79,
+            731.14
+        ],
+        "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/20926567527/job/60126219079",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219172"
+        },
+        "captured_info": {}
+    },
+    "models_bart": {
+        "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": 490,
+        "skipped": 326,
+        "time_spent": [
+            218.98,
+            219.66
+        ],
+        "error": false,
+        "failures": {},
+        "job_link": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219405",
+            "single": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219146"
+        },
+        "captured_info": {}
+    },
+    "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": 357,
+        "skipped": 217,
+        "time_spent": [
+            204.45,
+            205.14
+        ],
+        "error": false,
+        "failures": {},
+        "job_link": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219130",
+            "single": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219073"
+        },
+        "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": 349,
+        "skipped": 225,
+        "time_spent": [
+            82.08,
+            78.85
+        ],
+        "error": false,
+        "failures": {},
+        "job_link": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219075",
+            "single": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219137"
+        },
+        "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": 244,
+        "skipped": 252,
+        "time_spent": [
+            83.18,
+            81.43
+        ],
+        "error": false,
+        "failures": {
+            "single": [
+                {
+                    "line": "tests/models/big_bird/test_modeling_big_bird.py::BigBirdModelIntegrationTest::test_fill_mask",
+                    "trace": "(line 911)  AssertionError: '' != 'happiness'"
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/big_bird/test_modeling_big_bird.py::BigBirdModelIntegrationTest::test_fill_mask",
+                    "trace": "(line 911)  AssertionError: '' != 'happiness'"
+                }
+            ]
+        },
+        "job_link": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219225",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219102"
+        },
+        "captured_info": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219225#step:16:1",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219102#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": 385,
+        "skipped": 203,
+        "time_spent": [
+            945.77,
+            944.87
+        ],
+        "error": false,
+        "failures": {
+            "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']"
+                }
+            ],
+            "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']"
+                }
+            ]
+        },
+        "job_link": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219106",
+            "single": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219159"
+        },
+        "captured_info": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219106#step:16:1",
+            "single": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219159#step:16:1"
+        }
+    },
+    "models_gemma2": {
+        "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": 1,
+                "multi": 1
+            }
+        },
+        "errors": 0,
+        "success": 280,
+        "skipped": 212,
+        "time_spent": [
+            522.52,
+            634.89
+        ],
+        "error": false,
+        "failures": {
+            "multi": [
+                {
+                    "line": "[100%]",
+                    "trace": "(line 2779)  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": "Cannot retrieve error message."
+                }
+            ],
+            "single": [
+                {
+                    "line": "[100%]",
+                    "trace": "(line 2779)  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": "Cannot retrieve error message."
+                }
+            ]
+        },
+        "job_link": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219166",
+            "single": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219180"
+        },
+        "captured_info": {}
+    },
+    "models_gemma3": {
+        "failed": {
+            "PyTorch": {
+                "unclassified": 0,
+                "single": 6,
+                "multi": 6
+            },
+            "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": 586,
+        "skipped": 372,
+        "time_spent": [
+            557.93,
+            553.8
+        ],
+        "error": false,
+        "failures": {
+            "single": [
+                {
+                    "line": "tests/models/gemma3/test_modeling_gemma3.py::Gemma3TextModelTest::test_generation_beyond_sliding_window_tiny_model",
+                    "trace": "(line 151)  AssertionError: Tensor-likes are not equal!"
+                },
+                {
+                    "line": "tests/models/gemma3/test_modeling_gemma3.py::Gemma3IntegrationTest::test_dynamic_sliding_window_is_default",
+                    "trace": "(line 677)  AssertionError: 'DynamicSlidingWindowLayer' unexpectedly found in 'DynamicCache(layers=[DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer])'"
+                },
+                {
+                    "line": "tests/models/gemma3/test_modeling_gemma3.py::Gemma3IntegrationTest::test_export_text_only",
+                    "trace": "(line 677)  AssertionError: 'What[21 chars]ance? editarviles 콘 കേന്ദ്ര続くétricasétricas em[88 chars]िमों' != 'What[21 chars]ance?ępuje തരennelimegreen materiale トレーétrica[74 chars]rens'"
+                },
+                {
+                    "line": "tests/models/gemma3/test_modeling_gemma3.py::Gemma3IntegrationTest::test_generation_beyond_sliding_window_1_sdpa",
+                    "trace": "(line 3400)  UnboundLocalError: local variable 'tb' referenced before assignment"
+                },
+                {
+                    "line": "tests/models/gemma3/test_modeling_gemma3.py::Gemma3IntegrationTest::test_generation_beyond_sliding_window_2_eager",
+                    "trace": "(line 3400)  UnboundLocalError: local variable 'tb' referenced before assignment"
+                },
+                {
+                    "line": "tests/models/gemma3/test_modeling_gemma3.py::Gemma3IntegrationTest::test_model_1b_text_only",
+                    "trace": "(line 677)  AssertionError: Lists differ: [\"Write a poem about Machine Learning. sub[159 chars]ctr\"] != ['Write a poem about Machine Learning.\\n\\n[108 chars],\\n']"
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/gemma3/test_modeling_gemma3.py::Gemma3TextModelTest::test_generation_beyond_sliding_window_tiny_model",
+                    "trace": "(line 151)  AssertionError: Tensor-likes are not equal!"
+                },
+                {
+                    "line": "tests/models/gemma3/test_modeling_gemma3.py::Gemma3IntegrationTest::test_dynamic_sliding_window_is_default",
+                    "trace": "(line 677)  AssertionError: 'DynamicSlidingWindowLayer' unexpectedly found in 'DynamicCache(layers=[DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer, DynamicLayer, DynamicSlidingWindowLayer, DynamicSlidingWindowLayer])'"
+                },
+                {
+                    "line": "tests/models/gemma3/test_modeling_gemma3.py::Gemma3IntegrationTest::test_export_text_only",
+                    "trace": "(line 677)  AssertionError: 'What[21 chars]ance? editarviles 콘 കേന്ദ്ര続くétricasétricas em[88 chars]िमों' != 'What[21 chars]ance?ępuje തരennelimegreen materiale トレーétrica[74 chars]rens'"
+                },
+                {
+                    "line": "tests/models/gemma3/test_modeling_gemma3.py::Gemma3IntegrationTest::test_generation_beyond_sliding_window_1_sdpa",
+                    "trace": "(line 3400)  UnboundLocalError: local variable 'tb' referenced before assignment"
+                },
+                {
+                    "line": "tests/models/gemma3/test_modeling_gemma3.py::Gemma3IntegrationTest::test_generation_beyond_sliding_window_2_eager",
+                    "trace": "(line 3400)  UnboundLocalError: local variable 'tb' referenced before assignment"
+                },
+                {
+                    "line": "tests/models/gemma3/test_modeling_gemma3.py::Gemma3IntegrationTest::test_model_1b_text_only",
+                    "trace": "(line 677)  AssertionError: Lists differ: [\"Write a poem about Machine Learning. sub[159 chars]ctr\"] != ['Write a poem about Machine Learning.\\n\\n[108 chars],\\n']"
+                }
+            ]
+        },
+        "job_link": {
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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_chat_template_return_assistant_tokens_mask",
+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                },
+                {
+                    "line": "tests/models/llama/test_tokenization_llama.py::LlamaTokenizationTest::test_chat_template_return_assistant_tokens_mask_truncated",
+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                },
+                {
+                    "line": "tests/models/llama/test_tokenization_llama.py::LlamaTokenizationTest::test_padding_side_in_kwargs",
+                    "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."
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/llama/test_tokenization_llama.py::LlamaTokenizationTest::test_added_tokens_serialization",
+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                },
+                {
+                    "line": "tests/models/llama/test_tokenization_llama.py::LlamaTokenizationTest::test_chat_template_return_assistant_tokens_mask",
+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                },
+                {
+                    "line": "tests/models/llama/test_tokenization_llama.py::LlamaTokenizationTest::test_chat_template_return_assistant_tokens_mask_truncated",
+                    "trace": "(line 483)  OSError: You are trying to access a gated repo."
+                },
+                {
+                    "line": "tests/models/llama/test_tokenization_llama.py::LlamaTokenizationTest::test_padding_side_in_kwargs",
+                    "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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+            "Quantization": {
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+                "single": 0,
+                "multi": 0
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+            "Unclassified": {
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+                "single": 0,
+                "multi": 0
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+            293.2,
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+        "error": false,
+        "failures": {
+            "single": [
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_generation_siglip_backbone",
+                    "trace": "(line 631)  AssertionError: 'user[25 chars]stantConditionsent优于是非是非人家 draw人家 Acceler𝜃墉 no[81 chars]ller' != 'user[25 chars]stant The image shows two cats, one on the lef[84 chars] cat'"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_pixtral",
+                    "trace": "(line 692)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 140.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 90.69 MiB is free. Process 17501 has 22.21 GiB memory in use. Of the allocated memory 21.82 GiB is allocated by PyTorch, and 4.11 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_4bit",
+                    "trace": "(line 692)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1.25 GiB. GPU 0 has a total capacity of 22.30 GiB of which 522.69 MiB is free. Process 17501 has 21.79 GiB memory in use. Of the allocated memory 21.39 GiB is allocated by PyTorch, and 8.05 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_tokenizer_integration",
+                    "trace": "(line 589)  AssertionError: Lists differ: ['<|im_start|>', 'sy', 'st', 'em', '\\n', 'An', 'sw', 'er', ' [245 chars]'\\n'] != ['<|im_start|>', 'system', '\\n', 'Answer', '▁the', '▁question[173 chars]'\\n']"
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_generation_siglip_backbone",
+                    "trace": "(line 631)  AssertionError: 'user[25 chars]stantConditionsent优于是非是非人家 draw人家 Acceler𝜃墉 no[81 chars]ller' != 'user[25 chars]stant The image shows two cats, one on the lef[84 chars] cat'"
+                },
+                {
+                    "line": "tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_pixtral",
+                    "trace": "(line 692)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 140.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 92.69 MiB is free. Process 22420 has 22.21 GiB memory in use. Of the allocated memory 21.69 GiB is allocated by PyTorch, and 12.11 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_4bit",
+                    "trace": "(line 692)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1.25 GiB. GPU 0 has a total capacity of 22.30 GiB of which 300.69 MiB is free. Process 22420 has 22.00 GiB memory in use. Of the allocated memory 21.13 GiB is allocated by PyTorch, and 380.92 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_tokenizer_integration",
+                    "trace": "(line 589)  AssertionError: Lists differ: ['<|im_start|>', 'sy', 'st', 'em', '\\n', 'An', 'sw', 'er', ' [245 chars]'\\n'] != ['<|im_start|>', 'system', '\\n', 'Answer', '▁the', '▁question[173 chars]'\\n']"
+                }
+            ]
+        },
+        "job_link": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219205",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219216"
+        },
+        "captured_info": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219205#step:16:1",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219216#step:16:1"
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+                    "line": "tests/models/llava_next_video/test_modeling_llava_next_video.py::LlavaNextVideoForConditionalGenerationIntegrationTest::test_small_model_integration_test",
+                    "trace": "(line 134)  RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::Half != c10::BFloat16"
+                },
+                {
+                    "line": "tests/models/llava_next_video/test_modeling_llava_next_video.py::LlavaNextVideoForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch",
+                    "trace": "(line 134)  RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::Half != c10::BFloat16"
+                },
+                {
+                    "line": "tests/models/llava_next_video/test_modeling_llava_next_video.py::LlavaNextVideoForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch_different_vision_types",
+                    "trace": "(line 134)  RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::Half != c10::BFloat16"
+                },
+                {
+                    "line": "tests/models/llava_next_video/test_modeling_llava_next_video.py::LlavaNextVideoForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch_matches_single",
+                    "trace": "(line 134)  RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::Half != c10::BFloat16"
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/llava_next_video/test_modeling_llava_next_video.py::LlavaNextVideoForConditionalGenerationIntegrationTest::test_small_model_integration_test",
+                    "trace": "(line 134)  RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::Half != c10::BFloat16"
+                },
+                {
+                    "line": "tests/models/llava_next_video/test_modeling_llava_next_video.py::LlavaNextVideoForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch",
+                    "trace": "(line 134)  RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::Half != c10::BFloat16"
+                },
+                {
+                    "line": "tests/models/llava_next_video/test_modeling_llava_next_video.py::LlavaNextVideoForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch_different_vision_types",
+                    "trace": "(line 134)  RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::Half != c10::BFloat16"
+                },
+                {
+                    "line": "tests/models/llava_next_video/test_modeling_llava_next_video.py::LlavaNextVideoForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch_matches_single",
+                    "trace": "(line 134)  RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::Half != c10::BFloat16"
+                }
+            ]
+        },
+        "job_link": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/20926567527/job/60126219224",
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+                    "line": "tests/models/paligemma/test_modeling_paligemma.py::PaliGemmaForConditionalGenerationIntegrationTest::test_integration_detection_bug",
+                    "trace": "(line 677)  AssertionError: 'detect shoe\\n<loc0045><loc0309><loc0708><loc0646> shoe' != 'detect shoe\\n<loc0051><loc0309><loc0708><loc0646> shoe'"
+                },
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+                    "line": "tests/models/paligemma/test_modeling_paligemma.py::PaliGemmaForConditionalGenerationIntegrationTest::test_paligemma_finetuning_with_suffixes_bf16",
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+                    "trace": "(line 677)  AssertionError: Lists differ: ['ans[13 chars]is the cow standing?\\nbeach', '\\n a cow standing on the beach'] != ['ans[13 chars]is the cow standing?\\nbeach', '\\ncow on the beach']"
+                },
+                {
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+                    "trace": "(line 677)  AssertionError: Lists differ: ['ans[13 chars]is the cow standing?\\nbeach', '\\n a cow standing on the beach'] != ['ans[13 chars]is the cow standing?\\nbeach', '\\ncow on the beach']"
+                },
+                {
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+                    "trace": "(line 677)  AssertionError: Lists differ: ['ans[13 chars]is the cow standing?\\nbeach', '\\n a cow standing on the beach'] != ['ans[13 chars]is the cow standing?\\nbeach', '\\ncow on the beach']"
+                }
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+                },
+                {
+                    "line": "tests/models/paligemma/test_modeling_paligemma.py::PaliGemmaForConditionalGenerationIntegrationTest::test_paligemma_finetuning_with_suffixes_bf16",
+                    "trace": "(line 613)  AssertionError: assert False"
+                },
+                {
+                    "line": "tests/models/paligemma/test_modeling_paligemma.py::PaliGemmaForConditionalGenerationIntegrationTest::test_small_model_integration_test_paligemma_batched",
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+                },
+                {
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+                },
+                {
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