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hakrami
/
emotionv2

Text Classification
Transformers
Safetensors
llama
trl
sft
text-embeddings-inference
4-bit precision
bitsandbytes
Model card Files Files and versions
xet
Community

Instructions to use hakrami/emotionv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use hakrami/emotionv2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="hakrami/emotionv2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("hakrami/emotionv2")
    model = AutoModelForSequenceClassification.from_pretrained("hakrami/emotionv2")
  • Notebooks
  • Google Colab
  • Kaggle
emotionv2
4.31 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
hakrami's picture
hakrami
Upload tokenizer
7ec74dc verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    5.18 kB
    Upload LlamaForSequenceClassification about 2 years ago
  • added_tokens.json
    635 Bytes
    Upload tokenizer about 2 years ago
  • config.json
    2.4 kB
    Upload LlamaForSequenceClassification about 2 years ago
  • model.safetensors
    4.3 GB
    xet
    Upload LlamaForSequenceClassification about 2 years ago
  • special_tokens_map.json
    548 Bytes
    Upload tokenizer about 2 years ago
  • tokenizer.json
    1.85 MB
    Upload tokenizer about 2 years ago
  • tokenizer.model
    500 kB
    xet
    Upload tokenizer about 2 years ago
  • tokenizer_config.json
    5.81 kB
    Upload tokenizer about 2 years ago