Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
sentiment-analysis
text-embeddings-inference
Instructions to use DerivedFunction01/distilroberta-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DerivedFunction01/distilroberta-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DerivedFunction01/distilroberta-imdb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DerivedFunction01/distilroberta-imdb") model = AutoModelForSequenceClassification.from_pretrained("DerivedFunction01/distilroberta-imdb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1ee9f0c27a2680b2a9ec370def669be36e05e079b35e3a54e2af024ced2bbab
- Size of remote file:
- 5.2 kB
- SHA256:
- 880cc71c5b7eed1df686a7a4215ef139d9cdf7d007b1e699a4490ad173b2599a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.