Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use SteveWCG/roberta-sentence-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SteveWCG/roberta-sentence-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SteveWCG/roberta-sentence-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SteveWCG/roberta-sentence-classifier") model = AutoModelForSequenceClassification.from_pretrained("SteveWCG/roberta-sentence-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from SteveWCG/roberta-sentence-classifier: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
-
https://huggingface.co/SteveWCG/roberta-sentence-classifier/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://SteveWCG/roberta-sentence-classifier@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/SteveWCG/roberta-sentence-classifier/resolve/refs%2Fpr%2F1/tokenizer.json
3.56 MB
File too large to display, you can check the raw version instead.