Instructions to use Prasann15479/sec_train_model_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prasann15479/sec_train_model_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Prasann15479/sec_train_model_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Prasann15479/sec_train_model_classification") model = AutoModelForSequenceClassification.from_pretrained("Prasann15479/sec_train_model_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f58247932f4213faac041d07894c080ddb5544dbb53f335e843a30b03a423044
- Size of remote file:
- 11.4 MB
- SHA256:
- 0a018134fd4ea264da6ed1c1b00e4b36533af34a96780e2333ed9f6779a215f7
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