Text Classification
Transformers
Safetensors
PyTorch
English
bert
sentiment-analysis
nlp
Eval Results (legacy)
text-embeddings-inference
Instructions to use abhiprd2000/nlp-sentiment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abhiprd2000/nlp-sentiment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abhiprd2000/nlp-sentiment-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abhiprd2000/nlp-sentiment-model") model = AutoModelForSequenceClassification.from_pretrained("abhiprd2000/nlp-sentiment-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add cross-language evaluation matrix (4-model × 4-language study)
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