Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use agi-css/distilroberta-base-mrl-sym with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agi-css/distilroberta-base-mrl-sym with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="agi-css/distilroberta-base-mrl-sym")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("agi-css/distilroberta-base-mrl-sym") model = AutoModelForSequenceClassification.from_pretrained("agi-css/distilroberta-base-mrl-sym") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6548f1a1023403e53fba9c9e3061cff75bbacf10c88caecb7320d7c89c000f49
- Size of remote file:
- 3.06 kB
- SHA256:
- 213943460391f6ced451b53d2eea66463bb12fd31d9d3f36ca873efbcd3885d2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.