Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use xshubhamx/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xshubhamx/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xshubhamx/roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xshubhamx/roberta-base") model = AutoModelForSequenceClassification.from_pretrained("xshubhamx/roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00c21d7799c65baa49803e5b0a079ef4acf59b681dbf2c02ee480d0775bff4d1
- Size of remote file:
- 997 MB
- SHA256:
- f4bf2a5fb5c51a9e167f7c7ca181d5c9ef8e5aaa6dc5e1bcb06480c6f2eaf545
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