Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use anitha67/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anitha67/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anitha67/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anitha67/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("anitha67/my_awesome_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d616fac50c6b5fc6ecff897511a58cadf4271319718d1671bdd7dd83f962c7e
- Size of remote file:
- 268 MB
- SHA256:
- 18f0ad4ac71e35bc677bd4db566dc78bad62b58cb515ea0f18b3520ad6d9887f
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