Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use FrinzTheCoder/xlm-roberta-base-orm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FrinzTheCoder/xlm-roberta-base-orm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FrinzTheCoder/xlm-roberta-base-orm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FrinzTheCoder/xlm-roberta-base-orm") model = AutoModelForSequenceClassification.from_pretrained("FrinzTheCoder/xlm-roberta-base-orm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from FrinzTheCoder/xlm-roberta-base-orm: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/FrinzTheCoder/xlm-roberta-base-orm/resolve/main/training_args.bin
- Command line
-
hf download hf://FrinzTheCoder/xlm-roberta-base-orm/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/FrinzTheCoder/xlm-roberta-base-orm/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 4da49da44a4910ab5b6c987d28a647a166e5f3784ce863c37494f0025c3e628e
- Size of remote file:
- 5.37 kB
- SHA256:
- c1a79038003e0dc41bd6dd3caf4fa825440b4c52727dae834b0b6ada4836c2c6
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