Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use ankushjamthikar/aj_first_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ankushjamthikar/aj_first_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ankushjamthikar/aj_first_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ankushjamthikar/aj_first_model") model = AutoModelForSequenceClassification.from_pretrained("ankushjamthikar/aj_first_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ae669245bf7fd794752fd630578651c9d5e079e602c5b43f08fd82f9934f484
- Size of remote file:
- 268 MB
- SHA256:
- d6c1a775294e001993b02870c731fd292f602fd83d2f793aa9edf1c76240fb07
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