Upload folder using huggingface_hub

internvl-eep0108/checkpoints/steps_5000_pytorch_model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:da808ea81aa88e03cdd6919412723e643c5ff6dde6b1ab5b0047b6f19510d3f7
+size 2620087086

internvl-eep0108/config.json

@@ -0,0 +1,87 @@
+{
+  "run_id": "internvlAdapter-0108-eep",
+  "run_root_dir": "/data/LumosVLA/LumosVLA/results",
+  "seed": 42,
+  "trackers": [
+    "jsonl",
+    "wandb"
+  ],
+  "wandb_entity": "xspadex-nanyang-technological-university-singapore",
+  "wandb_project": "internvl-eep-0108",
+  "is_debug": false,
+  "framework": {
+    "name": "internvlAdapter",
+    "qwenvl": {
+      "base_vlm": "/data/LumosVLA/LumosVLA/playground/internvl",
+      "attn_implementation": "flash_attention_2",
+      "vl_hidden_dim": 2048
+    },
+    "action_model": {
+      "action_model_type": "VLA-Adapter",
+      "hidden_dim": 2048,
+      "action_dim": 20,
+      "state_dim": 20,
+      "action_query_num": 64,
+      "use_pro_version": true,
+      "use_proprio": true,
+      "phase": "Training",
+      "num_actions_chunk": 30
+    },
+    "framework_py": "internvlAdapter"
+  },
+  "datasets": {
+    "vla_data": {
+      "dataset_py": "lerobot_datasets",
+      "data_root_dir": "/data/LumosVLA/LumosVLA/data/0106_data_10_in_1",
+      "data_mix": "train_0107eep",
+      "per_device_batch_size": 32,
+      "num_workers": 4,
+      "action_type": "abs_ee",
+      "image_size": 256
+    }
+  },
+  "trainer": {
+    "epochs": 100,
+    "max_train_steps": 15000,
+    "num_warmup_steps": 1000,
+    "save_interval": 2500,
+    "eval_interval": 100000,
+    "learning_rate": {
+      "base": 5e-05,
+      "intern_vl_interface": 1e-05,
+      "action_model": 0.0002
+    },
+    "lr_scheduler_type": "cosine_with_min_lr",
+    "scheduler_specific_kwargs": {
+      "min_lr": 1e-07
+    },
+    "freeze_modules": "intern_vl_interface.model.vision_model",
+    "loss_scale": {
+      "vla": 1.0,
+      "vlm": 0.05
+    },
+    "max_grad_norm": 1.0,
+    "warmup_ratio": 0.1,
+    "weight_decay": 0.0,
+    "logging_frequency": 10,
+    "gradient_clipping": 1.0,
+    "gradient_accumulation_steps": 1,
+    "optimizer": {
+      "name": "AdamW",
+      "betas": [
+        0.9,
+        0.95
+      ],
+      "eps": 1e-08,
+      "weight_decay": 0
+    }
+  },
+  "is_resume": false,
+  "resume_epoch": null,
+  "resume_step": null,
+  "enable_gradient_checkpointing": true,
+  "enable_mixed_precision_training": true,
+  "report_to": "wandb",
+  "wandb_run_name": "v1",
+  "output_dir": "/data/LumosVLA/LumosVLA/results/internvlAdapter-0108-eep"
+}

internvl-eep0108/config.yaml

@@ -0,0 +1,73 @@
+run_id: internvlAdapter-0108-eep
+run_root_dir: /data/LumosVLA/LumosVLA/results
+seed: 42
+trackers:
+- jsonl
+- wandb
+wandb_entity: xspadex-nanyang-technological-university-singapore
+wandb_project: internvl-eep-0108
+is_debug: false
+framework:
+  name: internvlAdapter
+  qwenvl:
+    base_vlm: /data/LumosVLA/LumosVLA/playground/internvl
+    attn_implementation: flash_attention_2
+    vl_hidden_dim: 2048
+  action_model:
+    action_model_type: VLA-Adapter
+    hidden_dim: 2048
+    action_dim: 20
+    state_dim: 20
+    action_query_num: 64
+    use_pro_version: true
+    use_proprio: true
+    phase: Training
+    num_actions_chunk: 30
+  framework_py: internvlAdapter
+datasets:
+  vla_data:
+    dataset_py: lerobot_datasets
+    data_root_dir: /data/LumosVLA/LumosVLA/data/0106_data_10_in_1
+    data_mix: train_0107eep
+    per_device_batch_size: 32
+    num_workers: 4
+    action_type: abs_ee
+    image_size: 256
+trainer:
+  epochs: 100
+  max_train_steps: 15000
+  num_warmup_steps: 1000
+  save_interval: 2500
+  eval_interval: 100000
+  learning_rate:
+    base: 5.0e-05
+    intern_vl_interface: 1.0e-05
+    action_model: 0.0002
+  lr_scheduler_type: cosine_with_min_lr
+  scheduler_specific_kwargs:
+    min_lr: 1.0e-07
+  freeze_modules: intern_vl_interface.model.vision_model
+  loss_scale:
+    vla: 1.0
+    vlm: 0.05
+  max_grad_norm: 1.0
+  warmup_ratio: 0.1
+  weight_decay: 0.0
+  logging_frequency: 10
+  gradient_clipping: 1.0
+  gradient_accumulation_steps: 1
+  optimizer:
+    name: AdamW
+    betas:
+    - 0.9
+    - 0.95
+    eps: 1.0e-08
+    weight_decay: 0
+is_resume: false
+resume_epoch: null
+resume_step: null
+enable_gradient_checkpointing: true
+enable_mixed_precision_training: true
+report_to: wandb
+wandb_run_name: v1
+output_dir: /data/LumosVLA/LumosVLA/results/internvlAdapter-0108-eep

internvl-eep0108/dataset_statistics.json

@@ -0,0 +1,218 @@
+{
+  "new_embodiment": {
+    "action": {
+      "mean": [
+        0.23282504230737688,
+        -0.05165965789929033,
+        0.21386985182762147,
+        -91.47970352172852,
+        20.121428585052488,
+        42.44750967025757,
+        0.23724629282951357,
+        0.08887637909501792,
+        0.21939275562763214,
+        45.390340900421144,
+        29.264903831481938,
+        -119.05479431152344,
+        0.03987310770899058,
+        0.03885028753429652
+      ],
+      "std": [
+        0.09953932969670672,
+        0.1263747541518203,
+        0.07284480907274637,
+        133.6138685971796,
+        18.383623797067543,
+        155.94565103777856,
+        0.10225355728400369,
+        0.08295887480529306,
+        0.06472772608178973,
+        158.29364115016972,
+        16.00381071103632,
+        97.27639744542212,
+        0.026943868199832993,
+        0.02694874948904217
+      ],
+      "max": [
+        0.5771363973617554,
+        0.5499705076217651,
+        1.1769417524337769,
+        179.99998474121094,
+        89.99874114990234,
+        179.9999237060547,
+        0.5673798322677612,
+        0.5647112131118774,
+        0.6844663023948669,
+        179.99998474121094,
+        89.99887084960938,
+        179.99996948242188,
+        0.05999999865889549,
+        0.05999999865889549
+      ],
+      "min": [
+        -0.15116086602210999,
+        -0.5200218558311462,
+        0.050602782517671585,
+        -180.0,
+        -20.672367095947266,
+        -179.99993896484375,
+        -0.0248020701110363,
+        -0.29858818650245667,
+        0.06846695393323898,
+        -179.99998474121094,
+        -13.50222110748291,
+        -179.9997100830078,
+        0.0,
+        0.0
+      ],
+      "q01": [
+        0.05501473695039749,
+        -0.3686788082122803,
+        0.0868777185678482,
+        -179.78305053710938,
+        -9.416550636291504,
+        -179.69680786132812,
+        0.056286852806806564,
+        -0.18694551289081573,
+        0.10547168552875519,
+        -179.8378448486328,
+        -0.19658219814300537,
+        -179.51170349121094,
+        0.0,
+        0.0
+      ],
+      "q99": [
+        0.47519516944885254,
+        0.4694986939430237,
+        0.46994128823280334,
+        179.755126953125,
+        89.57238006591797,
+        179.736328125,
+        0.48799216747283936,
+        0.3558615446090698,
+        0.43878117203712463,
+        179.83042907714844,
+        89.67033386230469,
+        179.49917602539062,
+        0.05999999865889549,
+        0.05999999865889549
+      ],
+      "mask": [
+        true,
+        true,
+        true,
+        true,
+        true,
+        true,
+        true,
+        true,
+        true,
+        true,
+        true,
+        true,
+        false,
+        false
+      ]
+    },
+    "state": {
+      "mean": [
+        0.24175260961055758,
+        -0.049470676161581656,
+        0.21608835756778721,
+        -1.413518315553665,
+        0.428703111410141,
+        0.7577013611793519,
+        0.24074497371912004,
+        0.08981470651924611,
+        0.21937729418277743,
+        0.8831917621195315,
+        0.6019748389720918,
+        -2.0126270771026613,
+        0.04148903861641884,
+        0.03994188271462917
+      ],
+      "std": [
+        0.09280708088090048,
+        0.12742504567945281,
+        0.0744079447762679,
+        2.5498722585501863,
+        0.3793943873796246,
+        2.808145353959299,
+        0.09863927576384764,
+        0.0815411369762193,
+        0.06492154445492224,
+        2.805201274470533,
+        0.31938597693868265,
+        1.884995382965943,
+        0.025358022526895105,
+        0.026140522839142637
+      ],
+      "max": [
+        0.5393329858779907,
+        0.48442599177360535,
+        0.6967939734458923,
+        3.1415927410125732,
+        1.5707963705062866,
+        3.1415927410125732,
+        0.5489550232887268,
+        0.44545501470565796,
+        0.6456500291824341,
+        3.1415927410125732,
+        1.5707963705062866,
+        3.1415927410125732,
+        0.06159999966621399,
+        0.05998999997973442
+      ],
+      "min": [
+        -0.10788500308990479,
+        -0.5191159844398499,
+        0.05315700173377991,
+        -3.1410515308380127,
+        -1.5302174091339111,
+        -3.1410515308380127,
+        -0.02319999970495701,
+        -0.26581600308418274,
+        0.06903599947690964,
+        -3.1410515308380127,
+        -0.23581144213676453,
+        -3.1410515308380127,
+        0.00014000000373926014,
+        7.000000186963007e-05
+      ],
+      "q01": [
+        0.056127000600099564,
+        -0.36912801861763,
+        0.08751751482486725,
+        -3.137159585952759,
+        -0.16739033162593842,
+        -3.1360411643981934,
+        0.056008998304605484,
+        -0.15914200246334076,
+        0.10651859641075134,
+        -3.138237953186035,
+        -0.005713686812669039,
+        -3.131770372390747,
+        0.0004199999966658652,
+        7.000000186963007e-05
+      ],
+      "q99": [
+        0.4720889925956726,
+        0.4121397137641907,
+        0.4779260456562042,
+        3.1415927410125732,
+        1.5365502834320068,
+        3.1415927410125732,
+        0.4841437041759491,
+        0.35178446769714355,
+        0.42531776428222656,
+        3.1415927410125732,
+        1.5435858964920044,
+        3.1415927410125732,
+        0.059780001640319824,
+        0.05992000177502632
+      ]
+    },
+    "num_transitions": 885334,
+    "num_trajectories": 881
+  }
+}

internvl-eep0108/wandb/wandb/run-20260108_200012-i9xan194/files/config.yaml

@@ -0,0 +1,119 @@
+_wandb:
+    value:
+        cli_version: 0.23.0
+        e:
+            xnqhd8cib93qg9k1a16qvlhxxdiv542f:
+                args:
+                    - --config_yaml
+                    - ./starVLA/config/training/starvla_train_internvl_adapter.yaml
+                    - --framework.framework_py
+                    - internvlAdapter
+                    - --framework.qwenvl.base_vlm
+                    - /data/LumosVLA/LumosVLA/playground/internvl
+                    - --run_id
+                    - internvlAdapter-0108-eep
+                    - --trainer.freeze_modules
+                    - intern_vl_interface.model.vision_model
+                    - --report_to
+                    - wandb
+                    - --wandb_project
+                    - internvl-eep-0108
+                    - --wandb_entity
+                    - xspadex-nanyang-technological-university-singapore
+                    - --wandb_run_name
+                    - v1
+                codePath: starVLA/training/train_starvla.py
+                codePathLocal: starVLA/training/train_starvla.py
+                cpu_count: 64
+                cpu_count_logical: 128
+                cudaVersion: "12.4"
+                disk:
+                    /:
+                        total: "1887976378368"
+                        used: "1675918073856"
+                email: 1293310705@qq.com
+                executable: /home/panda/miniconda3/envs/starVLA/bin/python3
+                git:
+                    commit: b1f785aa8a3440122218c0aac85769b802dadadc
+                    remote: https://gitee.com/jinfagang/LumosVLA.git
+                gpu: NVIDIA A800-SXM4-80GB
+                gpu_count: 8
+                gpu_nvidia:
+                    - architecture: Ampere
+                      cudaCores: 6912
+                      memoryTotal: "85899345920"
+                      name: NVIDIA A800-SXM4-80GB
+                      uuid: GPU-0d2b5d34-729e-280c-6053-d085eb99403b
+                    - architecture: Ampere
+                      cudaCores: 6912
+                      memoryTotal: "85899345920"
+                      name: NVIDIA A800-SXM4-80GB
+                      uuid: GPU-65f38011-3e70-9c1d-4fb8-5333e9d99b89
+                    - architecture: Ampere
+                      cudaCores: 6912
+                      memoryTotal: "85899345920"
+                      name: NVIDIA A800-SXM4-80GB
+                      uuid: GPU-5b46542e-b604-8bfd-af42-98d43c7d03bf
+                    - architecture: Ampere
+                      cudaCores: 6912
+                      memoryTotal: "85899345920"
+                      name: NVIDIA A800-SXM4-80GB
+                      uuid: GPU-3eeb053c-7fa9-6c1c-9d8a-2a6fe1b67362
+                    - architecture: Ampere
+                      cudaCores: 6912
+                      memoryTotal: "85899345920"
+                      name: NVIDIA A800-SXM4-80GB
+                      uuid: GPU-a184fe54-e17e-b157-a0e3-2a14ef3e57e0
+                    - architecture: Ampere
+                      cudaCores: 6912
+                      memoryTotal: "85899345920"
+                      name: NVIDIA A800-SXM4-80GB
+                      uuid: GPU-74a6c731-11c1-543e-0939-ab2040582ef6
+                    - architecture: Ampere
+                      cudaCores: 6912
+                      memoryTotal: "85899345920"
+                      name: NVIDIA A800-SXM4-80GB
+                      uuid: GPU-cbea7447-22c1-29f1-baf9-ce3ee61df04b
+                    - architecture: Ampere
+                      cudaCores: 6912
+                      memoryTotal: "85899345920"
+                      name: NVIDIA A800-SXM4-80GB
+                      uuid: GPU-0b8ddeb9-3777-1b93-d107-550cf75ccae8
+                host: bb936931da6f
+                memory:
+                    total: "2164152586240"
+                os: Linux-5.4.0-176-generic-x86_64-with-glibc2.31
+                program: /data/LumosVLA/LumosVLA/starVLA/training/train_starvla.py
+                python: CPython 3.10.19
+                root: /data/LumosVLA/LumosVLA/results/internvlAdapter-0108-eep/wandb
+                startedAt: "2026-01-08T12:00:12.226118Z"
+                writerId: xnqhd8cib93qg9k1a16qvlhxxdiv542f
+        m: []
+        python_version: 3.10.19
+        t:
+            "1":
+                - 1
+                - 11
+                - 41
+                - 49
+                - 63
+                - 71
+                - 80
+                - 83
+            "2":
+                - 1
+                - 11
+                - 41
+                - 49
+                - 63
+                - 71
+                - 80
+                - 83
+            "3":
+                - 13
+                - 61
+            "4": 3.10.19
+            "5": 0.23.0
+            "6": 4.57.0
+            "12": 0.23.0
+            "13": linux-x86_64

internvl-eep0108/wandb/wandb/run-20260108_200012-i9xan194/files/wandb-metadata.json

@@ -0,0 +1,109 @@
+{
+  "os": "Linux-5.4.0-176-generic-x86_64-with-glibc2.31",
+  "python": "CPython 3.10.19",
+  "startedAt": "2026-01-08T12:00:12.226118Z",
+  "args": [
+    "--config_yaml",
+    "./starVLA/config/training/starvla_train_internvl_adapter.yaml",
+    "--framework.framework_py",
+    "internvlAdapter",
+    "--framework.qwenvl.base_vlm",
+    "/data/LumosVLA/LumosVLA/playground/internvl",
+    "--run_id",
+    "internvlAdapter-0108-eep",
+    "--trainer.freeze_modules",
+    "intern_vl_interface.model.vision_model",
+    "--report_to",
+    "wandb",
+    "--wandb_project",
+    "internvl-eep-0108",
+    "--wandb_entity",
+    "xspadex-nanyang-technological-university-singapore",
+    "--wandb_run_name",
+    "v1"
+  ],
+  "program": "/data/LumosVLA/LumosVLA/starVLA/training/train_starvla.py",
+  "codePath": "starVLA/training/train_starvla.py",
+  "codePathLocal": "starVLA/training/train_starvla.py",
+  "git": {
+    "remote": "https://gitee.com/jinfagang/LumosVLA.git",
+    "commit": "b1f785aa8a3440122218c0aac85769b802dadadc"
+  },
+  "email": "1293310705@qq.com",
+  "root": "/data/LumosVLA/LumosVLA/results/internvlAdapter-0108-eep/wandb",
+  "host": "bb936931da6f",
+  "executable": "/home/panda/miniconda3/envs/starVLA/bin/python3",
+  "cpu_count": 64,
+  "cpu_count_logical": 128,
+  "gpu": "NVIDIA A800-SXM4-80GB",
+  "gpu_count": 8,
+  "disk": {
+    "/": {
+      "total": "1887976378368",
+      "used": "1675918073856"
+    }
+  },
+  "memory": {
+    "total": "2164152586240"
+  },
+  "gpu_nvidia": [
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-0d2b5d34-729e-280c-6053-d085eb99403b"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-65f38011-3e70-9c1d-4fb8-5333e9d99b89"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-5b46542e-b604-8bfd-af42-98d43c7d03bf"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-3eeb053c-7fa9-6c1c-9d8a-2a6fe1b67362"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-a184fe54-e17e-b157-a0e3-2a14ef3e57e0"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-74a6c731-11c1-543e-0939-ab2040582ef6"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-cbea7447-22c1-29f1-baf9-ce3ee61df04b"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-0b8ddeb9-3777-1b93-d107-550cf75ccae8"
+    }
+  ],
+  "cudaVersion": "12.4",
+  "writerId": "xnqhd8cib93qg9k1a16qvlhxxdiv542f"
+}

internvl-eep0108/wandb/wandb/run-20260108_200012-i9xan194/files/wandb-summary.json

@@ -0,0 +1 @@
+{"epoch":0.01,"_step":400,"_timestamp":1.7678763707166314e+09,"action_dit_loss":0.37962278723716736,"data_time":0.0017396584153175354,"learning_rate":8e-05,"model_time":3.702992856502533,"_wandb":{"runtime":2805},"_runtime":2805.242701426}

internvl-eep0108/wandb/wandb/run-20260108_205202-e9cszzl2/files/wandb-metadata.json

@@ -0,0 +1,109 @@
+{
+  "os": "Linux-5.4.0-176-generic-x86_64-with-glibc2.31",
+  "python": "CPython 3.10.19",
+  "startedAt": "2026-01-08T12:52:02.727244Z",
+  "args": [
+    "--config_yaml",
+    "./starVLA/config/training/starvla_train_internvl_adapter.yaml",
+    "--framework.framework_py",
+    "internvlAdapter",
+    "--framework.qwenvl.base_vlm",
+    "/data/LumosVLA/LumosVLA/playground/internvl",
+    "--run_id",
+    "internvlAdapter-0108-eep",
+    "--trainer.freeze_modules",
+    "intern_vl_interface.model.vision_model",
+    "--report_to",
+    "wandb",
+    "--wandb_project",
+    "internvl-eep-0108",
+    "--wandb_entity",
+    "xspadex-nanyang-technological-university-singapore",
+    "--wandb_run_name",
+    "v1"
+  ],
+  "program": "/data/LumosVLA/LumosVLA/starVLA/training/train_starvla.py",
+  "codePath": "starVLA/training/train_starvla.py",
+  "codePathLocal": "starVLA/training/train_starvla.py",
+  "git": {
+    "remote": "https://gitee.com/jinfagang/LumosVLA.git",
+    "commit": "b1f785aa8a3440122218c0aac85769b802dadadc"
+  },
+  "email": "1293310705@qq.com",
+  "root": "/data/LumosVLA/LumosVLA/results/internvlAdapter-0108-eep/wandb",
+  "host": "bb936931da6f",
+  "executable": "/home/panda/miniconda3/envs/starVLA/bin/python3",
+  "cpu_count": 64,
+  "cpu_count_logical": 128,
+  "gpu": "NVIDIA A800-SXM4-80GB",
+  "gpu_count": 8,
+  "disk": {
+    "/": {
+      "total": "1887976378368",
+      "used": "1675922972672"
+    }
+  },
+  "memory": {
+    "total": "2164152586240"
+  },
+  "gpu_nvidia": [
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-0d2b5d34-729e-280c-6053-d085eb99403b"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-65f38011-3e70-9c1d-4fb8-5333e9d99b89"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-5b46542e-b604-8bfd-af42-98d43c7d03bf"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-3eeb053c-7fa9-6c1c-9d8a-2a6fe1b67362"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-a184fe54-e17e-b157-a0e3-2a14ef3e57e0"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-74a6c731-11c1-543e-0939-ab2040582ef6"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-cbea7447-22c1-29f1-baf9-ce3ee61df04b"
+    },
+    {
+      "name": "NVIDIA A800-SXM4-80GB",
+      "memoryTotal": "85899345920",
+      "cudaCores": 6912,
+      "architecture": "Ampere",
+      "uuid": "GPU-0b8ddeb9-3777-1b93-d107-550cf75ccae8"
+    }
+  ],
+  "cudaVersion": "12.4",
+  "writerId": "1hdz3k3j0vc7spivw8hozglao68szjjt"
+}