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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af8d6958dd2ac67e7b408cbe2226fa70d28901df78af750ea0a774db8186f36c
- Size of remote file:
- 1.11 GB
- SHA256:
- c8b5cdde74fc8c2c8045e3a1642877a4ca883137a330345c119e20a9d8cfc8f8
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