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SenaSoft
/
chdv-sentiment-analysis

Text Classification
PEFT
Safetensors
Transformers
bert
lora
sentiment-analysis
spanish
social-media
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use SenaSoft/chdv-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use SenaSoft/chdv-sentiment-analysis with PEFT:

    Task type is invalid.
  • Transformers

    How to use SenaSoft/chdv-sentiment-analysis with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="SenaSoft/chdv-sentiment-analysis")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("SenaSoft/chdv-sentiment-analysis")
    model = AutoModelForSequenceClassification.from_pretrained("SenaSoft/chdv-sentiment-analysis")
  • Notebooks
  • Google Colab
  • Kaggle
chdv-sentiment-analysis
673 MB
Ctrl+K
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  • 1 contributor
History: 8 commits
SenaSoft's picture
SenaSoft
Update README.md
8bd5847 verified 8 months ago
  • .gitattributes
    1.52 kB
    initial commit 8 months ago
  • README.md
    5.48 kB
    Update README.md 8 months ago
  • config.json
    1.08 kB
    Upload BertForSequenceClassification 8 months ago
  • model.safetensors
    669 MB
    xet
    Upload BertForSequenceClassification 8 months ago
  • special_tokens_map.json
    132 Bytes
    Upload tokenizer 8 months ago
  • tokenizer.json
    2.56 MB
    Upload tokenizer 8 months ago
  • tokenizer_config.json
    1.35 kB
    Upload tokenizer 8 months ago
  • vocab.txt
    872 kB
    Upload tokenizer 8 months ago