Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use pabagcha/finetuning-sentiment-model-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pabagcha/finetuning-sentiment-model-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pabagcha/finetuning-sentiment-model-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pabagcha/finetuning-sentiment-model-1") model = AutoModelForSequenceClassification.from_pretrained("pabagcha/finetuning-sentiment-model-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ec472f4e64043ff6142a11ccb6a936bb89daaec2f0d481ac5510c58e13eadae
- Size of remote file:
- 499 MB
- SHA256:
- 7d78e56f90b9231bf86fd74b37cebfd7cd70ec1fd20d306e11c46f578036d37b
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