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
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

Jedida
/
tweet_sentiments_analysis_distilbert

Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use Jedida/tweet_sentiments_analysis_distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Jedida/tweet_sentiments_analysis_distilbert with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Jedida/tweet_sentiments_analysis_distilbert")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Jedida/tweet_sentiments_analysis_distilbert")
    model = AutoModelForSequenceClassification.from_pretrained("Jedida/tweet_sentiments_analysis_distilbert")
  • Notebooks
  • Google Colab
  • Kaggle
tweet_sentiments_analysis_distilbert / runs
15.3 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 11 commits
Jedida's picture
Jedida
End of training
96a1cfb almost 3 years ago
  • Jul23_16-10-38_ca36039d8ddb
    Training in progress, epoch 5 almost 3 years ago
  • Jul24_17-59-28_d5adbd708875
    End of training almost 3 years ago