Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use dpazmino/finetuning-sentiment-model_duke_final_two with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dpazmino/finetuning-sentiment-model_duke_final_two with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dpazmino/finetuning-sentiment-model_duke_final_two")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dpazmino/finetuning-sentiment-model_duke_final_two") model = AutoModelForSequenceClassification.from_pretrained("dpazmino/finetuning-sentiment-model_duke_final_two", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae9499450aa8743ca436078a225455815ed4a979ef52e36716b21f322b9cfa84
- Size of remote file:
- 268 MB
- SHA256:
- ac2a7a3fa74229c9e3535eaa37b7274823e5238c864ddc2845b4c63a7ed1499d
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