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nkarthikeyan
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IubNet

Safetensors
cnn
Model card Files Community

UCI Adult Data Analysis model using Tensorflow

Version: 0.1

Short Description: UCI Adult Data analysis using Tensorflow for demonstration of Patra Model Cards.

Full Description: We have trained a ML model using the tensorflow framework to predict income for the UCI Adult Dataset. We leverage this data to run the Patra model cards to capture metadata about the model as well as fairness and explainability metrics.

Keywords: uci adult, tensorflow, explainability, fairness, patra

Author: Your Name

Input Type: Tabular

Category: classification

Foundational Model: None

Input Data: https://archive.ics.uci.edu/ml/datasets/adult

Output Data: https://github.iu.edu/d2i/dockerhub/tensorflow/adult_modelv01

AI Model

Name: Income prediction tensorflow model

Version: 0.1

Description: Census classification problem using TensorFlow Neural Network using the UCI Adult Dataset

Owner: Your Name or Organization

Location: https://example.com/path-to-model

License: BSD-3 Clause

Framework: tensorflow

Model Type: dnn

Test Accuracy: 0.7919545769691467

Model Structure 

{
    "module": "keras",
    "class_name": "Sequential",
    "config": {
        "name": "sequential",
        "trainable": true,
        "dtype": {
            "module": "keras",
            "class_name": "DTypePolicy",
            "config": {
                "name": "float32"
            }
        },
        "layers": [
            {
                "module": "keras.layers",
                "class_name": "InputLayer",
                "config": {
                    "batch_shape": [
                        100
                    ],
                    "dtype": "float32",
                    "sparse": false,
                    "name": "input_layer"
                }
            },
            {
                "module": "keras.layers",
                "class_name": "Dense",
                "config": {
                    "name": "dense",
                    "trainable": true,
                    "dtype": {
                        "module": "keras",
                        "class_name": "DTypePolicy",
                        "config": {
                            "name": "float32"
                        }
                    },
                    "units": 64,
                    "activation": "relu",
                    "use_bias": true,
                    "kernel_initializer": {
                        "module": "keras.initializers",
                        "class_name": "GlorotUniform",
                        "config": {}
                    },
                    "bias_initializer": {
                        "module": "keras.initializers",
                        "class_name": "Zeros",
                        "config": {}
                    }
                },
                "build_config": {
                    "input_shape": [
                        100
                    ]
                }
            },
            {
                "module": "keras.layers",
                "class_name": "Dense",
                "config": {
                    "name": "dense_1",
                    "trainable": true,
                    "dtype": {
                        "module": "keras",
                        "class_name": "DTypePolicy",
                        "config": {
                            "name": "float32"
                        }
                    },
                    "units": 128,
                    "activation": "relu",
                    "use_bias": true,
                    "kernel_initializer": {
                        "module": "keras.initializers",
                        "class_name": "GlorotUniform",
                        "config": {}
                    },
                    "bias_initializer": {
                        "module": "keras.initializers",
                        "class_name": "Zeros",
                        "config": {}
                    }
                },
                "build_config": {
                    "input_shape": [
                        64
                    ]
                }
            },
            {
                "module": "keras.layers",
                "class_name": "Dense",
                "config": {
                    "name": "dense_2",
                    "trainable": true,
                    "dtype": {
                        "module": "keras",
                        "class_name": "DTypePolicy",
                        "config": {
                            "name": "float32"
                        }
                    },
                    "units": 64,
                    "activation": "relu",
                    "use_bias": true,
                    "kernel_initializer": {
                        "module": "keras.initializers",
                        "class_name": "GlorotUniform",
                        "config": {}
                    },
                    "bias_initializer": {
                        "module": "keras.initializers",
                        "class_name": "Zeros",
                        "config": {}
                    }
                },
                "build_config": {
                    "input_shape": [
                        128
                    ]
                }
            },
            {
                "module": "keras.layers",
                "class_name": "Dense",
                "config": {
                    "name": "dense_3",
                    "trainable": true,
                    "dtype": {
                        "module": "keras",
                        "class_name": "DTypePolicy",
                        "config": {
                            "name": "float32"
                        }
                    },
                    "units": 1,
                    "activation": "sigmoid",
                    "use_bias": true,
                    "kernel_initializer": {
                        "module": "keras.initializers",
                        "class_name": "GlorotUniform",
                        "config": {}
                    },
                    "bias_initializer": {
                        "module": "keras.initializers",
                        "class_name": "Zeros",
                        "config": {}
                    }
                },
                "build_config": {
                    "input_shape": [
                        64
                    ]
                }
            }
        ],
        "build_input_shape": [
            100
        ]
    },
    "build_config": {
        "input_shape": [
            100
        ]
    },
    "compile_config": {
        "optimizer": {
            "module": "keras.optimizers",
            "class_name": "Adam",
            "config": {
                "name": "adam",
                "learning_rate": 0.0010000000474974513,
                "use_ema": false,
                "ema_momentum": 0.99,
                "beta_1": 0.9,
                "beta_2": 0.999,
                "epsilon": 1e-07,
                "amsgrad": false
            }
        },
        "loss": "binary_crossentropy",
        "metrics": [
            "accuracy"
        ],
        "run_eagerly": false,
        "steps_per_execution": 1,
        "jit_compile": false
    }
}

Metrics

  • Test loss: 0.5084354877471924
  • Epochs: 100
  • Batch Size: 32
  • Optimizer: Adam
  • Learning Rate: 0.001
  • Input Shape: (26048, 100)

Bias Analysis

  • demographic_parity_diff: 0.032400848225782965
  • equal_odds_difference: 0.03417438108252019

Explainability Analysis

  • capital_gain: 0.14158532669974697
  • fnlwgt: 0.015681726452377108
  • age: 0.00021690960559580313
  • hours_per_week: 0.00013091093136204657
  • relationship__Not_in_family: 7.917947239345974e-05
  • marital_status__Married_civ_spouse: 7.522924906677672e-05
  • education__HS_grad: 5.9253134661254366e-05
  • occupation__Exec_managerial: 5.8465765582191924e-05
  • marital_status__Never_married: 2.9966458678243015e-05
  • education_num: 2.848242719968154e-05

Model Requirements

  • absl-py==1.4.0
  • accelerate==1.2.1
  • aiohappyeyeballs==2.4.4
  • aiohttp==3.11.11
  • aiosignal==1.3.2
  • alabaster==1.0.0
  • albucore==0.0.19
  • albumentations==1.4.20
  • ale-py==0.10.1
  • altair==5.5.0
  • annotated-types==0.7.0
  • anyio==3.7.1
  • argon2-cffi-bindings==21.2.0
  • argon2-cffi==23.1.0
  • array-record==0.6.0
  • arviz==0.20.0
  • astropy-iers-data==0.2025.1.27.0.32.44
  • astropy==6.1.7
  • astunparse==1.6.3
  • atpublic==4.1.0
  • attrs==25.1.0
  • audioread==3.0.1
  • autocommand==2.2.2
  • autograd==1.7.0
  • babel==2.16.0
  • backcall==0.2.0
  • backports.tarfile==1.2.0
  • beautifulsoup4==4.12.3
  • bigframes==1.33.0
  • bigquery-magics==0.5.0
  • bleach==6.2.0
  • blinker==1.9.0
  • blis==0.7.11
  • blosc2==3.0.0
  • bokeh==3.6.2
  • bottleneck==1.4.2
  • bqplot==0.12.44
  • branca==0.8.1
  • cachecontrol==0.14.2
  • cachetools==5.5.1
  • catalogue==2.0.10
  • certifi==2024.12.14
  • cffi==1.17.1
  • chardet==5.2.0
  • charset-normalizer==3.4.1
  • chex==0.1.88
  • clarabel==0.9.0
  • click==8.1.8
  • cloudpathlib==0.20.0
  • cloudpickle==3.1.1
  • cmake==3.31.4
  • cmdstanpy==1.2.5
  • colorcet==3.1.0
  • colorlover==0.3.0
  • colour==0.1.5
  • community==1.0.0b1
  • confection==0.1.5
  • cons==0.4.6
  • contourpy==1.3.1
  • cramjam==2.9.1
  • cryptography==43.0.3
  • cuda-python==12.6.0
  • cudf-cu12==24.12.0
  • cufflinks==0.17.3
  • cupy-cuda12x==13.3.0
  • cvxopt==1.3.2
  • cvxpy==1.6.0
  • cycler==0.12.1
  • cyipopt==1.5.0
  • cymem==2.0.11
  • cython==3.0.11
  • dask==2024.10.0
  • datascience==0.17.6
  • db-dtypes==1.4.0
  • dbus-python==1.2.18
  • debugpy==1.8.0
  • decorator==4.4.2
  • defusedxml==0.7.1
  • deprecated==1.2.18
  • diffusers==0.32.2
  • distro==1.9.0
  • dlib==19.24.2
  • dm-tree==0.1.8
  • docker-pycreds==0.4.0
  • docstring-parser==0.16
  • docutils==0.21.2
  • dopamine-rl==4.1.2
  • duckdb==1.1.3
  • earthengine-api==1.4.6
  • easydict==1.13
  • editdistance==0.8.1
  • eerepr==0.1.0
  • einops==0.8.0
  • en-core-web-sm==3.7.1
  • entrypoints==0.4
  • et-xmlfile==2.0.0
  • etils==1.11.0
  • etuples==0.3.9
  • eval-type-backport==0.2.2
  • farama-notifications==0.0.4
  • fastai==2.7.18
  • fastcore==1.7.28
  • fastdownload==0.0.7
  • fastjsonschema==2.21.1
  • fastprogress==1.0.3
  • fastrlock==0.8.3
  • filelock==3.17.0
  • firebase-admin==6.6.0
  • flask==3.1.0
  • flatbuffers==25.1.24
  • flax==0.10.2
  • folium==0.19.4
  • fonttools==4.55.6
  • frozendict==2.4.6
  • frozenlist==1.5.0
  • fsspec==2024.10.0
  • future==1.0.0
  • gast==0.6.0
  • gcsfs==2024.10.0
  • gdal==3.6.4
  • gdown==5.2.0
  • geemap==0.35.1
  • gensim==4.3.3
  • geocoder==1.38.1
  • geographiclib==2.0
  • geopandas==1.0.1
  • geopy==2.4.1
  • gin-config==0.5.0
  • gitdb==4.0.12
  • gitpython==3.1.44
  • glob2==0.7
  • google-ai-generativelanguage==0.6.15
  • google-api-core==2.19.2
  • google-api-python-client==2.155.0
  • google-auth-httplib2==0.2.0
  • google-auth-oauthlib==1.2.1
  • google-auth==2.27.0
  • google-cloud-aiplatform==1.74.0
  • google-cloud-bigquery-connection==1.17.0
  • google-cloud-bigquery-storage==2.27.0
  • google-cloud-bigquery==3.25.0
  • google-cloud-bigtable==2.28.1
  • google-cloud-core==2.4.1
  • google-cloud-datastore==2.20.2
  • google-cloud-firestore==2.19.0
  • google-cloud-functions==1.19.0
  • google-cloud-iam==2.17.0
  • google-cloud-language==2.16.0
  • google-cloud-pubsub==2.25.0
  • google-cloud-resource-manager==1.14.0
  • google-cloud-spanner==3.51.0
  • google-cloud-storage==2.19.0
  • google-cloud-translate==3.19.0
  • google-colab==1.0.0
  • google-crc32c==1.6.0
  • google-genai==0.3.0
  • google-generativeai==0.8.4
  • google-pasta==0.2.0
  • google-resumable-media==2.7.2
  • google==2.0.3
  • googleapis-common-protos==1.66.0
  • googledrivedownloader==0.4
  • graphviz==0.20.3
  • greenlet==3.1.1
  • grpc-google-iam-v1==0.14.0
  • grpc-interceptor==0.15.4
  • grpcio-status==1.62.3
  • grpcio==1.70.0
  • gspread-dataframe==4.0.0
  • gspread==6.1.4
  • gym-notices==0.0.8
  • gym==0.25.2
  • gymnasium==1.0.0
  • h11==0.14.0
  • h5netcdf==1.5.0
  • h5py==3.12.1
  • highspy==1.9.0
  • holidays==0.65
  • holoviews==1.20.0
  • html5lib==1.1
  • httpcore==1.0.7
  • httpimport==1.4.0
  • httplib2==0.22.0
  • httpx==0.28.1
  • huggingface-hub==0.27.1
  • humanize==4.11.0
  • hyperopt==0.2.7
  • ibis-framework==9.2.0
  • idna==3.10
  • imageio-ffmpeg==0.6.0
  • imageio==2.36.1
  • imagesize==1.4.1
  • imbalanced-learn==0.13.0
  • imgaug==0.4.0
  • immutabledict==4.2.1
  • importlib-metadata==8.6.1
  • importlib-resources==6.5.2
  • imutils==0.5.4
  • inflect==7.5.0
  • iniconfig==2.0.0
  • intel-cmplr-lib-ur==2025.0.4
  • intel-openmp==2025.0.4
  • ipyevents==2.0.2
  • ipyfilechooser==0.6.0
  • ipykernel==5.5.6
  • ipyleaflet==0.19.2
  • ipyparallel==8.8.0
  • ipython-genutils==0.2.0
  • ipython-sql==0.5.0
  • ipython==7.34.0
  • ipytree==0.2.2
  • ipywidgets==7.7.1
  • itsdangerous==2.2.0
  • jaraco.collections==5.1.0
  • jaraco.context==5.3.0
  • jaraco.functools==4.0.1
  • jaraco.text==3.12.1
  • jax-cuda12-pjrt==0.4.33
  • jax-cuda12-plugin==0.4.33
  • jax==0.4.33
  • jaxlib==0.4.33
  • jeepney==0.7.1
  • jellyfish==1.1.0
  • jieba==0.42.1
  • jinja2==3.1.5
  • jiter==0.8.2
  • joblib==1.4.2
  • jsonpatch==1.33
  • jsonpickle==4.0.1
  • jsonpointer==3.0.0
  • jsonschema-specifications==2024.10.1
  • jsonschema==4.23.0
  • jupyter-client==6.1.12
  • jupyter-console==6.1.0
  • jupyter-core==5.7.2
  • jupyter-leaflet==0.19.2
  • jupyter-server==1.24.0
  • jupyterlab-pygments==0.3.0
  • jupyterlab-widgets==3.0.13
  • kaggle==1.6.17
  • kagglehub==0.3.6
  • keras==3.8.0
  • keyring==23.5.0
  • kiwisolver==1.4.8
  • langchain-core==0.3.31
  • langchain-text-splitters==0.3.5
  • langchain==0.3.15
  • langcodes==3.5.0
  • langsmith==0.3.1
  • language-data==1.3.0
  • launchpadlib==1.10.16
  • lazr.restfulclient==0.14.4
  • lazr.uri==1.0.6
  • lazy-loader==0.4
  • libclang==18.1.1
  • libcudf-cu12==24.12.0
  • libkvikio-cu12==24.12.1
  • librosa==0.10.2.post1
  • lightgbm==4.5.0
  • linkify-it-py==2.0.3
  • llvmlite==0.43.0
  • locket==1.0.0
  • logical-unification==0.4.6
  • lxml==5.3.0
  • marisa-trie==1.2.1
  • markdown-it-py==3.0.0
  • markdown==3.7
  • markupsafe==3.0.2
  • matplotlib-inline==0.1.7
  • matplotlib-venn==1.1.1
  • matplotlib==3.10.0
  • mdit-py-plugins==0.4.2
  • mdurl==0.1.2
  • minikanren==1.0.3
  • missingno==0.5.2
  • mistune==3.1.0
  • mizani==0.13.1
  • mkl==2025.0.1
  • ml-dtypes==0.4.1
  • mlxtend==0.23.4
  • more-itertools==10.5.0
  • moviepy==1.0.3
  • mpmath==1.3.0
  • msgpack==1.1.0
  • multidict==6.1.0
  • multipledispatch==1.0.0
  • multitasking==0.0.11
  • murmurhash==1.0.12
  • music21==9.3.0
  • namex==0.0.8
  • narwhals==1.24.0
  • natsort==8.4.0
  • nbclassic==1.2.0
  • nbclient==0.10.2
  • nbconvert==7.16.5
  • nbformat==5.10.4
  • ndindex==1.9.2
  • nest-asyncio==1.6.0
  • networkx==3.4.2
  • nibabel==5.3.2
  • nltk==3.9.1
  • notebook-shim==0.2.4
  • notebook==6.5.5
  • numba-cuda==0.0.17.1
  • numba==0.60.0
  • numexpr==2.10.2
  • numpy==1.26.4
  • nvidia-cublas-cu12==12.5.3.2
  • nvidia-cuda-cupti-cu12==12.5.82
  • nvidia-cuda-nvcc-cu12==12.5.82
  • nvidia-cuda-nvrtc-cu12==12.5.82
  • nvidia-cuda-runtime-cu12==12.5.82
  • nvidia-cudnn-cu12==9.3.0.75
  • nvidia-cufft-cu12==11.2.3.61
  • nvidia-curand-cu12==10.3.6.82
  • nvidia-cusolver-cu12==11.6.3.83
  • nvidia-cusparse-cu12==12.5.1.3
  • nvidia-nccl-cu12==2.21.5
  • nvidia-nvcomp-cu12==4.1.0.6
  • nvidia-nvjitlink-cu12==12.5.82
  • nvidia-nvtx-cu12==12.4.127
  • nvtx==0.2.10
  • nx-cugraph-cu12==24.12.0
  • oauth2client==4.1.3
  • oauthlib==3.2.2
  • openai==1.59.9
  • opencv-contrib-python==4.10.0.84
  • opencv-python-headless==4.11.0.86
  • opencv-python==4.10.0.84
  • openpyxl==3.1.5
  • opentelemetry-api==1.16.0
  • opentelemetry-sdk==1.16.0
  • opentelemetry-semantic-conventions==0.37b0
  • opt-einsum==3.4.0
  • optax==0.2.4
  • optree==0.14.0
  • orbax-checkpoint==0.6.4
  • orjson==3.10.15
  • osqp==0.6.7.post3
  • packaging==24.2
  • pandas-datareader==0.10.0
  • pandas-gbq==0.26.1
  • pandas-stubs==2.2.2.240909
  • pandas==2.2.2
  • pandocfilters==1.5.1
  • panel==1.6.0
  • param==2.2.0
  • parso==0.8.4
  • parsy==2.1
  • partd==1.4.2
  • pathlib==1.0.1
  • patra-toolkit==0.1.2
  • patsy==1.0.1
  • peewee==3.17.8
  • peft==0.14.0
  • pexpect==4.9.0
  • pickleshare==0.7.5
  • pillow==11.1.0
  • pip==24.1.2
  • platformdirs==4.3.6
  • plotly==5.24.1
  • plotnine==0.14.5
  • pluggy==1.5.0
  • ply==3.11
  • polars==1.9.0
  • pooch==1.8.2
  • portpicker==1.5.2
  • preshed==3.0.9
  • prettytable==3.13.0
  • proglog==0.1.10
  • progressbar2==4.5.0
  • prometheus-client==0.21.1
  • promise==2.3
  • prompt-toolkit==3.0.50
  • propcache==0.2.1
  • prophet==1.1.6
  • proto-plus==1.25.0
  • protobuf==4.25.6
  • psutil==5.9.5
  • psycopg2==2.9.10
  • ptyprocess==0.7.0
  • py-cpuinfo==9.0.0
  • py4j==0.10.9.7
  • pyarrow==17.0.0
  • pyasn1-modules==0.4.1
  • pyasn1==0.6.1
  • pycocotools==2.0.8
  • pycparser==2.22
  • pydantic-core==2.27.2
  • pydantic==2.10.6
  • pydata-google-auth==1.9.1
  • pydot==3.0.4
  • pydotplus==2.0.2
  • pydrive2==1.21.3
  • pydrive==1.3.1
  • pyerfa==2.0.1.5
  • pygame==2.6.1
  • pygit2==1.16.0
  • pygments==2.18.0
  • pygobject==3.42.1
  • pyjwt==2.10.1
  • pylibcudf-cu12==24.12.0
  • pylibcugraph-cu12==24.12.0
  • pylibraft-cu12==24.12.0
  • pymc==5.19.1
  • pymystem3==0.2.0
  • pynvjitlink-cu12==0.4.0
  • pyogrio==0.10.0
  • pyomo==6.8.2
  • pyopengl==3.1.9
  • pyopenssl==24.2.1
  • pyparsing==3.2.1
  • pyperclip==1.9.0
  • pyproj==3.7.0
  • pyshp==2.3.1
  • pysocks==1.7.1
  • pyspark==3.5.4
  • pytensor==2.26.4
  • pytest==8.3.4
  • python-apt==0.0.0
  • python-box==7.3.2
  • python-dateutil==2.8.2
  • python-louvain==0.16
  • python-slugify==8.0.4
  • python-snappy==0.7.3
  • python-utils==3.9.1
  • pytz==2024.2
  • pyviz-comms==3.0.4
  • pyyaml==6.0.2
  • pyzmq==24.0.1
  • qdldl==0.1.7.post5
  • ratelim==0.1.6
  • referencing==0.36.2
  • regex==2024.11.6
  • requests-oauthlib==1.3.1
  • requests-toolbelt==1.0.0
  • requests==2.32.3
  • requirements-parser==0.9.0
  • rich==13.9.4
  • rmm-cu12==24.12.1
  • rpds-py==0.22.3
  • rpy2==3.4.2
  • rsa==4.9
  • safetensors==0.5.2
  • scikit-image==0.25.1
  • scikit-learn==1.6.1
  • scipy==1.13.1
  • scooby==0.10.0
  • scs==3.2.7.post2
  • seaborn==0.13.2
  • secretstorage==3.3.1
  • send2trash==1.8.3
  • sentence-transformers==3.3.1
  • sentencepiece==0.2.0
  • sentry-sdk==2.20.0
  • setproctitle==1.3.4
  • setuptools==75.1.0
  • shapely==2.0.6
  • shellingham==1.5.4
  • simple-parsing==0.1.7
  • six==1.17.0
  • sklearn-compat==0.1.3
  • sklearn-pandas==2.2.0
  • slicer==0.0.8
  • smart-open==7.1.0
  • smmap==5.0.2
  • sniffio==1.3.1
  • snowballstemmer==2.2.0
  • soundfile==0.13.1
  • soupsieve==2.6
  • soxr==0.5.0.post1
  • spacy-legacy==3.0.12
  • spacy-loggers==1.0.5
  • spacy==3.7.5
  • spanner-graph-notebook==1.0.9
  • sphinx==8.1.3
  • sphinxcontrib-applehelp==2.0.0
  • sphinxcontrib-devhelp==2.0.0
  • sphinxcontrib-htmlhelp==2.1.0
  • sphinxcontrib-jsmath==1.0.1
  • sphinxcontrib-qthelp==2.0.0
  • sphinxcontrib-serializinghtml==2.0.0
  • sqlalchemy==2.0.37
  • sqlglot==25.6.1
  • sqlparse==0.5.3
  • srsly==2.5.1
  • stanio==0.5.1
  • statsmodels==0.14.4
  • stringzilla==3.11.3
  • sympy==1.13.1
  • tables==3.10.2
  • tabulate==0.9.0
  • tbb==2022.0.0
  • tcmlib==1.2.0
  • tenacity==9.0.0
  • tensorboard-data-server==0.7.2
  • tensorboard==2.18.0
  • tensorflow-datasets==4.9.7
  • tensorflow-hub==0.16.1
  • tensorflow-io-gcs-filesystem==0.37.1
  • tensorflow-metadata==1.16.1
  • tensorflow-probability==0.24.0
  • tensorflow==2.18.0
  • tensorstore==0.1.71
  • termcolor==2.5.0
  • terminado==0.18.1
  • text-unidecode==1.3
  • textblob==0.17.1
  • tf-keras==2.18.0
  • tf-slim==1.1.0
  • thinc==8.2.5
  • threadpoolctl==3.5.0
  • tifffile==2025.1.10
  • timm==1.0.14
  • tinycss2==1.4.0
  • tokenizers==0.21.0
  • toml==0.10.2
  • tomli==2.0.1
  • toolz==0.12.1
  • torch==2.5.1+cu124
  • torchaudio==2.5.1+cu124
  • torchsummary==1.5.1
  • torchvision==0.20.1+cu124
  • tornado==6.3.3
  • tqdm==4.67.1
  • traitlets==5.7.1
  • traittypes==0.2.1
  • transformers==4.47.1
  • triton==3.1.0
  • tweepy==4.14.0
  • typeguard==4.4.1
  • typer==0.15.1
  • types-pytz==2024.2.0.20241221
  • types-setuptools==75.8.0.20250110
  • typing-extensions==4.12.2
  • tzdata==2025.1
  • tzlocal==5.2
  • uc-micro-py==1.0.3
  • umf==0.9.1
  • uritemplate==4.1.1
  • urllib3==2.3.0
  • vega-datasets==0.9.0
  • wadllib==1.3.6
  • wandb==0.19.4
  • wasabi==1.1.3
  • wcwidth==0.2.13
  • weasel==0.4.1
  • webcolors==24.11.1
  • webencodings==0.5.1
  • websocket-client==1.8.0
  • websockets==14.2
  • werkzeug==3.1.3
  • wheel==0.45.1
  • widgetsnbextension==3.6.10
  • wordcloud==1.9.4
  • wrapt==1.17.2
  • xarray-einstats==0.8.0
  • xarray==2025.1.1
  • xgboost==2.1.3
  • xlrd==2.0.1
  • xyzservices==2025.1.0
  • yarl==1.18.3
  • yellowbrick==1.5
  • yfinance==0.2.52
  • zipp==3.21.0
  • zstandard==0.23.0
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Safetensors
Model size
422k params
Tensor type
F32
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