Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use achDev/reberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use achDev/reberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="achDev/reberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("achDev/reberta") model = AutoModelForSequenceClassification.from_pretrained("achDev/reberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f077be07abb91ed75b6146001ac8d3218def78d7e8d75e493f696b022c227c5
- Size of remote file:
- 17.1 MB
- SHA256:
- f1cc44ad7faaeec47241864835473fd5403f2da94673f3f764a77ebcb0a803ec
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