Datasets:

bniladridas
/

nvidia-gpu-dataset

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Dataset Viewer

The dataset viewer is not available for this dataset.

Cannot get the config names for the dataset.

Error code:   RetryableConfigNamesError
Exception:    HfHubHTTPError
Message:      500 Server Error: Internal Server Error for url: https://huggingface.co/api/datasets/bniladridas/nvidia-gpu-dataset/tree/89fc0ac1583f079431d2480fb4f21d533e8d9152/nvidia-gpu-dataset?recursive=True&expand=False (Request ID: Root=1-67cd7629-657867fd28d592a2574e0bb2;b9714cb4-6901-4cc9-9f03-fc2be22b773f)

Internal Error - We're working hard to fix this as soon as possible!
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 164, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1731, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1688, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1066, in get_module
                  patterns = get_data_patterns(base_path, download_config=self.download_config)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 501, in get_data_patterns
                  return _get_data_files_patterns(resolver)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 295, in _get_data_files_patterns
                  data_files = pattern_resolver(pattern)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 388, in resolve_pattern
                  for filepath, info in fs.glob(pattern, detail=True, **glob_kwargs).items()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 521, in glob
                  return super().glob(path, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 604, in glob
                  allpaths = self.find(root, maxdepth=depth, withdirs=True, detail=True, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 563, in find
                  out = self._ls_tree(path, recursive=True, refresh=refresh, revision=resolved_path.revision, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 446, in _ls_tree
                  self._ls_tree(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 463, in _ls_tree
                  for path_info in tree:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 3028, in list_repo_tree
                  for path_info in paginate(path=tree_url, headers=headers, params={"recursive": recursive, "expand": expand}):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_pagination.py", line 37, in paginate
                  hf_raise_for_status(r)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_http.py", line 477, in hf_raise_for_status
                  raise _format(HfHubHTTPError, str(e), response) from e
              huggingface_hub.errors.HfHubHTTPError: 500 Server Error: Internal Server Error for url: https://huggingface.co/api/datasets/bniladridas/nvidia-gpu-dataset/tree/89fc0ac1583f079431d2480fb4f21d533e8d9152/nvidia-gpu-dataset?recursive=True&expand=False (Request ID: Root=1-67cd7629-657867fd28d592a2574e0bb2;b9714cb4-6901-4cc9-9f03-fc2be22b773f)
              
              Internal Error - We're working hard to fix this as soon as possible!

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

🚫 Hands Off! This dataset’s locked down—no downloading or messing with it unless you’re cleared. Regular Hugging Face users, this ain’t for you.

NVIDIA GPU Scraper

This project crunches NVIDIA GPU data in a slick Docker setup. It scrapes the web with webscraped.py, then whips up a tidy report with summary.py. Think CSV gold like nvidia_gpu_summary_report.csv.

What You Need

Docker on your machine.
Basic command-line chops.

Quick Start

Project Layout

nvidia_project/
├── Dockerfile
├── requirements.txt
├── webscraped.py
├── summary.py
└── README.md

1. Build It

Fire up the Docker image—all dependencies baked in, no virtualenv nonsense:

docker build -t nvidia_project .

2. Run It

Spin the container and let the scripts rip:

docker run --rm -it nvidia_project

--rm: Cleans up after itself.
-it: Keeps you in the loop with a terminal.

3. Grab the Goods

Snag the output CSV from the container:

docker cp $(docker ps -l -q):/app/nvidia_gpu_summary_report.csv /your/local/path

Example:

docker cp $(docker ps -l -q):/app/nvidia_gpu_summary_report.csv /Users/niladridas/Desktop/nvidia_doc

Pushing to Hugging Face

Want it on Hugging Face? Here’s the drill:

Get the Tools:
```
pip install datasets
```
Prep the Data: Make sure it’s in JSON or CSV shape.

Upload It:

huggingface-cli dataset create --dataset_name bniladridas/nvidia-gpu-dataset --path /path/to/your/data

(Swap bniladridas/nvidia-gpu-dataset for your own dataset name if needed.)

Spice It Up: Add a dataset card with the juicy details.
Check It: Hit Hugging Face to confirm it’s live and legit.

More deets? Peek at the Hugging Face docs.

Debugging

Stuff breaking? Dive in:

Peek Inside:

docker run -it nvidia_project /bin/sh

Scope out /app with:

ls -l /app

Read the Tea Leaves:
```
docker logs $(docker ps -l -q)
```

Pro Tips

Docker’s Your Friend: No need to fuss with source .venv/bin/activate—it’s all contained.
Keep it lean—let the container handle the heavy lifting.
Double-check your Dockerfile copies webscraped.py and summary.py to /app and sets the entrypoint right.
Tweak that docker cp path to wherever you want the CSV to land.

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