Text Classification
Transformers
PyTorch
TensorFlow
Rust
Safetensors
English
distilbert
Eval Results (legacy)
Instructions to use HARSHU550/Sentiments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HARSHU550/Sentiments with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HARSHU550/Sentiments")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HARSHU550/Sentiments") model = AutoModelForSequenceClassification.from_pretrained("HARSHU550/Sentiments") - Notebooks
- Google Colab
- Kaggle
Upload 4 files
Browse files- model.safetensors +3 -0
- pytorch_model (1).bin +3 -0
- rust_model.ot +3 -0
- tf_model.h5 +3 -0
model.safetensors
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