Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use khilan-crest/twitter-roberta-base-sentiment-latest_22012025T171349 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use khilan-crest/twitter-roberta-base-sentiment-latest_22012025T171349 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="khilan-crest/twitter-roberta-base-sentiment-latest_22012025T171349")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("khilan-crest/twitter-roberta-base-sentiment-latest_22012025T171349") model = AutoModelForSequenceClassification.from_pretrained("khilan-crest/twitter-roberta-base-sentiment-latest_22012025T171349") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dee64f9ce8c043add67a628189ab675e671208a4572c04b3a0024bf14922a70b
- Size of remote file:
- 499 MB
- SHA256:
- 9d1822f5134d7dd88f1e7db0a9a3f4fb5adcf8c9d91a6f6f9d3818497defc659
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.