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bmdavis
/
my-language-model

Text Classification
Transformers
Safetensors
English
distilbert
sentiment-analysis
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use bmdavis/my-language-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use bmdavis/my-language-model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="bmdavis/my-language-model")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("bmdavis/my-language-model")
    model = AutoModelForSequenceClassification.from_pretrained("bmdavis/my-language-model", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
my-language-model / results
2.41 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
bmdavis's picture
bmdavis
Add trained sentiment model and tokenizer
611dbe2 about 1 year ago
  • checkpoint-250
    Add trained sentiment model and tokenizer about 1 year ago
  • checkpoint-500
    Add trained sentiment model and tokenizer about 1 year ago
  • checkpoint-750
    Add trained sentiment model and tokenizer about 1 year ago