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AI Energy Score Project 14

meta-llama/Llama-3.2-1B

COMPLETED

Text Generation

v0

cardiffnlp/twitter-roberta-base-sentiment-latest

FAILED

Text Classification

v0

/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884 warnings.warn( Downloading readme: 0%| | 0.00/271 [00:00<?, ?B/s] Downloading readme: 100%|██████████| 271/271 [00:00<00:00, 2.73MB/s] Downloading data: 0%| | 0.00/453k [00:00<?, ?B/s] Downloading data: 100%|██████████| 453k/453k [00:00<00:00, 2.83MB/s] Downloading data: 100%|██████████| 453k/453k [00:00<00:00, 2.83MB/s] Generating train split: 0%| | 0/1000 [00:00<?, ? examples/s] Generating train split: 100%|██████████| 1000/1000 [00:00<00:00, 201368.48 examples/s] [codecarbon INFO @ 23:20:33] [setup] RAM Tracking... [codecarbon INFO @ 23:20:33] [setup] GPU Tracking... [codecarbon INFO @ 23:20:33] Tracking Nvidia GPU via pynvml [codecarbon DEBUG @ 23:20:33] GPU available. Starting setup [codecarbon INFO @ 23:20:33] [setup] CPU Tracking... [codecarbon DEBUG @ 23:20:33] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget [codecarbon DEBUG @ 23:20:33] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux [codecarbon DEBUG @ 23:20:33] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics [codecarbon WARNING @ 23:20:33] No CPU tracking mode found. Falling back on CPU constant mode. [codecarbon WARNING @ 23:20:34] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us. [codecarbon INFO @ 23:20:34] CPU Model on constant consumption mode: AMD EPYC 7R32 [codecarbon INFO @ 23:20:34] >>> Tracker's metadata: [codecarbon INFO @ 23:20:34] Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35 [codecarbon INFO @ 23:20:34] Python version: 3.9.20 [codecarbon INFO @ 23:20:34] CodeCarbon version: 2.5.1 [codecarbon INFO @ 23:20:34] Available RAM : 186.705 GB [codecarbon INFO @ 23:20:34] CPU count: 48 [codecarbon INFO @ 23:20:34] CPU model: AMD EPYC 7R32 [codecarbon INFO @ 23:20:34] GPU count: 1 [codecarbon INFO @ 23:20:34] GPU model: 1 x NVIDIA A10G [codecarbon DEBUG @ 23:20:35] Not running on AWS [codecarbon DEBUG @ 23:20:36] Not running on Azure [codecarbon DEBUG @ 23:20:37] Not running on GCP [codecarbon INFO @ 23:20:37] Saving emissions data to file /runs/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-10-07-23-20-25/codecarbon.csv [codecarbon DEBUG @ 23:20:38] EmissionsData(timestamp='2024-10-07T23:20:38', project_name='codecarbon', run_id='0e4bc046-c4df-4e48-866a-9a8d99e426db', duration=0.0031156789045780897, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0) Filter: 0%| | 0/1000 [00:00<?, ? examples/s] Filter: 100%|██████████| 1000/1000 [00:00<00:00, 159984.13 examples/s] Running tokenizer on dataset: 0%| | 0/1000 [00:00<?, ? examples/s] Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 2691.27 examples/s] Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 2667.25 examples/s] [codecarbon INFO @ 23:20:38] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.27353525161743164 W [codecarbon DEBUG @ 23:20:38] RAM : 0.27 W during 0.41 s [measurement time: 0.0005] [codecarbon INFO @ 23:20:38] Energy consumed for all GPUs : 0.000007 kWh. Total GPU Power : 65.45066620881586 W [codecarbon DEBUG @ 23:20:38] GPU : 65.45 W during 0.41 s [measurement time: 0.0022] [codecarbon INFO @ 23:20:38] Energy consumed for all CPUs : 0.000005 kWh. Total CPU Power : 42.5 W [codecarbon DEBUG @ 23:20:38] CPU : 42.50 W during 0.41 s [measurement time: 0.0000] [codecarbon INFO @ 23:20:38] 0.000012 kWh of electricity used since the beginning. [codecarbon DEBUG @ 23:20:38] last_duration=0.40900541795417666 ------------------------ [codecarbon DEBUG @ 23:20:38] EmissionsData(timestamp='2024-10-07T23:20:38', project_name='codecarbon', run_id='0e4bc046-c4df-4e48-866a-9a8d99e426db', duration=0.4121430969098583, emissions=4.5573209828862485e-06, emissions_rate=1.1057618135681164e-05, cpu_power=42.5, gpu_power=65.45066620881586, ram_power=0.27353525161743164, cpu_energy=4.864328597775764e-06, gpu_energy=7.450561515298659e-06, ram_energy=3.1077252325416766e-08, energy_consumed=1.234596736539984e-05, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0) [codecarbon DEBUG @ 23:20:38] EmissionsData(timestamp='2024-10-07T23:20:38', project_name='codecarbon', run_id='0e4bc046-c4df-4e48-866a-9a8d99e426db', duration=0.002233574981801212, emissions=4.5573209828862485e-06, emissions_rate=0.002040370715117479, cpu_power=42.5, gpu_power=65.45066620881586, ram_power=0.27353525161743164, cpu_energy=4.864328597775764e-06, gpu_energy=7.450561515298659e-06, ram_energy=3.1077252325416766e-08, energy_consumed=1.234596736539984e-05, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0) 0%| | 0/1000 [00:00<?, ?it/s] 1%|▏ | 14/1000 [00:00<00:07, 137.21it/s]/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [516,0,0], thread: [32,0,0] Assertion `srcIndex < srcSelectDimSize` failed. /opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [516,0,0], thread: [33,0,0] Assertion `srcIndex < srcSelectDimSize` failed. /opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [516,0,0], thread: [34,0,0] Assertion `srcIndex < srcSelectDimSize` failed. /opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [516,0,0], thread: [35,0,0] Assertion `srcIndex < srcSelectDimSize` failed. /opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [516,0,0], thread: [36,0,0] Assertion `srcIndex < srcSelectDimSize` failed. 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launch(experiment_config=experiment_config) File "/optimum-benchmark/optimum_benchmark/experiment.py", line 102, in launch raise error File "/optimum-benchmark/optimum_benchmark/experiment.py", line 90, in launch report = launcher.launch(run, experiment_config.benchmark, experiment_config.backend) File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 47, in launch while not process_context.join(): File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 189, in join raise ProcessRaisedException(msg, error_index, failed_process.pid) torch.multiprocessing.spawn.ProcessRaisedException: -- Process 0 terminated with the following error: Traceback (most recent call last): File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 76, in _wrap fn(i, *args) File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 63, in entrypoint worker_output = worker(*worker_args) File "/optimum-benchmark/optimum_benchmark/experiment.py", line 62, in run benchmark.run(backend) File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 178, in run self.run_inference_energy_tracking(backend) File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 262, in run_inference_energy_tracking inputs = backend.prepare_inputs(inputs) File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 338, in prepare_inputs inputs[key] = value.to(self.config.device) RuntimeError: CUDA error: device-side assert triggered CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1 Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions. Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

cardiffnlp/twitter-roberta-base-sentiment-latest

FAILED

Text Generation

v0

/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884 warnings.warn( Downloading readme: 0%| | 0.00/271 [00:00<?, ?B/s] Downloading readme: 100%|██████████| 271/271 [00:00<00:00, 2.73MB/s] Downloading data: 0%| | 0.00/453k [00:00<?, ?B/s] Downloading data: 100%|██████████| 453k/453k [00:00<00:00, 2.83MB/s] Downloading data: 100%|██████████| 453k/453k [00:00<00:00, 2.83MB/s] Generating train split: 0%| | 0/1000 [00:00<?, ? examples/s] Generating train split: 100%|██████████| 1000/1000 [00:00<00:00, 201368.48 examples/s] [codecarbon INFO @ 23:20:33] [setup] RAM Tracking... [codecarbon INFO @ 23:20:33] [setup] GPU Tracking... [codecarbon INFO @ 23:20:33] Tracking Nvidia GPU via pynvml [codecarbon DEBUG @ 23:20:33] GPU available. Starting setup [codecarbon INFO @ 23:20:33] [setup] CPU Tracking... [codecarbon DEBUG @ 23:20:33] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget [codecarbon DEBUG @ 23:20:33] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux [codecarbon DEBUG @ 23:20:33] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics [codecarbon WARNING @ 23:20:33] No CPU tracking mode found. Falling back on CPU constant mode. [codecarbon WARNING @ 23:20:34] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us. [codecarbon INFO @ 23:20:34] CPU Model on constant consumption mode: AMD EPYC 7R32 [codecarbon INFO @ 23:20:34] >>> Tracker's metadata: [codecarbon INFO @ 23:20:34] Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35 [codecarbon INFO @ 23:20:34] Python version: 3.9.20 [codecarbon INFO @ 23:20:34] CodeCarbon version: 2.5.1 [codecarbon INFO @ 23:20:34] Available RAM : 186.705 GB [codecarbon INFO @ 23:20:34] CPU count: 48 [codecarbon INFO @ 23:20:34] CPU model: AMD EPYC 7R32 [codecarbon INFO @ 23:20:34] GPU count: 1 [codecarbon INFO @ 23:20:34] GPU model: 1 x NVIDIA A10G [codecarbon DEBUG @ 23:20:35] Not running on AWS [codecarbon DEBUG @ 23:20:36] Not running on Azure [codecarbon DEBUG @ 23:20:37] Not running on GCP [codecarbon INFO @ 23:20:37] Saving emissions data to file /runs/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-10-07-23-20-25/codecarbon.csv [codecarbon DEBUG @ 23:20:38] EmissionsData(timestamp='2024-10-07T23:20:38', project_name='codecarbon', run_id='0e4bc046-c4df-4e48-866a-9a8d99e426db', duration=0.0031156789045780897, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0) Filter: 0%| | 0/1000 [00:00<?, ? examples/s] Filter: 100%|██████████| 1000/1000 [00:00<00:00, 159984.13 examples/s] Running tokenizer on dataset: 0%| | 0/1000 [00:00<?, ? examples/s] Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 2691.27 examples/s] Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 2667.25 examples/s] [codecarbon INFO @ 23:20:38] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.27353525161743164 W [codecarbon DEBUG @ 23:20:38] RAM : 0.27 W during 0.41 s [measurement time: 0.0005] [codecarbon INFO @ 23:20:38] Energy consumed for all GPUs : 0.000007 kWh. Total GPU Power : 65.45066620881586 W [codecarbon DEBUG @ 23:20:38] GPU : 65.45 W during 0.41 s [measurement time: 0.0022] [codecarbon INFO @ 23:20:38] Energy consumed for all CPUs : 0.000005 kWh. Total CPU Power : 42.5 W [codecarbon DEBUG @ 23:20:38] CPU : 42.50 W during 0.41 s [measurement time: 0.0000] [codecarbon INFO @ 23:20:38] 0.000012 kWh of electricity used since the beginning. [codecarbon DEBUG @ 23:20:38] last_duration=0.40900541795417666 ------------------------ [codecarbon DEBUG @ 23:20:38] EmissionsData(timestamp='2024-10-07T23:20:38', project_name='codecarbon', run_id='0e4bc046-c4df-4e48-866a-9a8d99e426db', duration=0.4121430969098583, emissions=4.5573209828862485e-06, emissions_rate=1.1057618135681164e-05, cpu_power=42.5, gpu_power=65.45066620881586, ram_power=0.27353525161743164, cpu_energy=4.864328597775764e-06, gpu_energy=7.450561515298659e-06, ram_energy=3.1077252325416766e-08, energy_consumed=1.234596736539984e-05, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0) [codecarbon DEBUG @ 23:20:38] EmissionsData(timestamp='2024-10-07T23:20:38', project_name='codecarbon', run_id='0e4bc046-c4df-4e48-866a-9a8d99e426db', duration=0.002233574981801212, emissions=4.5573209828862485e-06, emissions_rate=0.002040370715117479, cpu_power=42.5, gpu_power=65.45066620881586, ram_power=0.27353525161743164, cpu_energy=4.864328597775764e-06, gpu_energy=7.450561515298659e-06, ram_energy=3.1077252325416766e-08, energy_consumed=1.234596736539984e-05, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0) 0%| | 0/1000 [00:00<?, ?it/s] 1%|▏ | 14/1000 [00:00<00:07, 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/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [120,0,0] Assertion `srcIndex < srcSelectDimSize` failed. /opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [121,0,0] Assertion `srcIndex < srcSelectDimSize` failed. /opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [122,0,0] Assertion `srcIndex < srcSelectDimSize` failed. /opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [123,0,0] Assertion `srcIndex < srcSelectDimSize` failed. /opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [124,0,0] Assertion `srcIndex < srcSelectDimSize` failed. /opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [125,0,0] Assertion `srcIndex < srcSelectDimSize` failed. /opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [126,0,0] Assertion `srcIndex < srcSelectDimSize` failed. /opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [127,0,0] Assertion `srcIndex < srcSelectDimSize` failed. 2%|▏ | 22/1000 [00:00<00:07, 124.18it/s] Error executing job with overrides: ['backend.model=cardiffnlp/twitter-roberta-base-sentiment-latest', 'backend.processor=cardiffnlp/twitter-roberta-base-sentiment-latest'] Traceback (most recent call last): File "/optimum-benchmark/optimum_benchmark/cli.py", line 65, in benchmark_cli benchmark_report: BenchmarkReport = launch(experiment_config=experiment_config) File "/optimum-benchmark/optimum_benchmark/experiment.py", line 102, in launch raise error File "/optimum-benchmark/optimum_benchmark/experiment.py", line 90, in launch report = launcher.launch(run, experiment_config.benchmark, experiment_config.backend) File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 47, in launch while not process_context.join(): File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 189, in join raise ProcessRaisedException(msg, error_index, failed_process.pid) torch.multiprocessing.spawn.ProcessRaisedException: -- Process 0 terminated with the following error: Traceback (most recent call last): File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 76, in _wrap fn(i, *args) File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 63, in entrypoint worker_output = worker(*worker_args) File "/optimum-benchmark/optimum_benchmark/experiment.py", line 62, in run benchmark.run(backend) File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 178, in run self.run_inference_energy_tracking(backend) File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 262, in run_inference_energy_tracking inputs = backend.prepare_inputs(inputs) File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 338, in prepare_inputs inputs[key] = value.to(self.config.device) RuntimeError: CUDA error: device-side assert triggered CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1 Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions. Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

cardiffnlp/twitter-roberta-base-sentiment-latest

FAILED

Text Generation

v0

"/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning:(...TRUNCATED)

cardiffnlp/twitter-roberta-base-sentiment-latest

FAILED

Text Classification

v0

"/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning:(...TRUNCATED)

cardiffnlp/twitter-roberta-base-sentiment-latest

FAILED

Text Classification

v0

"/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning:(...TRUNCATED)

cardiffnlp/twitter-roberta-base-sentiment-latest

FAILED

Text Classification

v0

"/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning:(...TRUNCATED)

Emanuel/twitter-emotion-deberta-v3-base

FAILED

Text Classification

v0

"\nDownloading readme: 0%| | 0.00/271 [00:00<?, ?B/s]\nDownloading readme: 100%|███(...TRUNCATED)

distilbert/distilbert-base-uncased-finetuned-sst-2-english

COMPLETED

Text Classification

v0

"/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning:(...TRUNCATED)

distilbert/distilbert-base-uncased-finetuned-sst-2-english

COMPLETED

Text Classification

v0