Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

asogwa001
/
sentiment-imdb-models

Text Classification
Transformers
Joblib
ONNX
English
sentiment-analysis
Model card Files Files and versions
xet
Community

Instructions to use asogwa001/sentiment-imdb-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use asogwa001/sentiment-imdb-models with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="asogwa001/sentiment-imdb-models")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("asogwa001/sentiment-imdb-models", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
sentiment-imdb-models
512 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 8 commits
asogwa001's picture
asogwa001
docs: enable git lfs for large model files
67eeede 7 months ago
  • bert-tokenizer
    tokenizer: add bert-base tokenizer 7 months ago
  • .gitattributes
    1.57 kB
    docs: enable git lfs for large model files 7 months ago
  • README.md
    220 Bytes
    Update README.md 7 months ago
  • bert-base_sentiment_model.onnx
    1.22 MB
    xet
    bert-base: add finetuned model; trained for 3 epochs on i 3 epochs on imdb 7 months ago
  • bert-base_sentiment_model.onnx.data
    438 MB
    xet
    bert-base: add finetuned model; trained for 3 epochs on i 3 epochs on imdb 7 months ago
  • lr_sentiment_model.joblib

    Detected Pickle imports (4)

    • "joblib.numpy_pickle.NumpyArrayWrapper",
    • "numpy.dtype",
    • "numpy.ndarray",
    • "sklearn.linear_model._logistic.LogisticRegression"

    How to fix it?

    15.4 MB
    xet
    logistic-regression: add classic lr model trained on imdb 7 months ago
  • tfidf_vectorizer.joblib

    Detected Pickle imports (6)

    • "sklearn.feature_extraction.text.TfidfTransformer",
    • "numpy.dtype",
    • "numpy.float64",
    • "joblib.numpy_pickle.NumpyArrayWrapper",
    • "sklearn.feature_extraction.text.TfidfVectorizer",
    • "numpy.ndarray"

    How to fix it?

    56.6 MB
    xet
    logistic-regression: add tfidf vectorizer used for preprocessing text 7 months ago