Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use manjinder/sentiment_model_14mar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manjinder/sentiment_model_14mar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="manjinder/sentiment_model_14mar")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("manjinder/sentiment_model_14mar") model = AutoModelForSequenceClassification.from_pretrained("manjinder/sentiment_model_14mar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a27d33d58888d701573783ce05be081678a5f8b60145f4489686363c661b4ea3
- Size of remote file:
- 268 MB
- SHA256:
- 5033682a11ac8f32843bfda495ff58b6903f333b93a70cf509c8e2a4f7114b57
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