Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use pepppper/roberta-unfair with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pepppper/roberta-unfair with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pepppper/roberta-unfair")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pepppper/roberta-unfair") model = AutoModelForSequenceClassification.from_pretrained("pepppper/roberta-unfair", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from pepppper/roberta-unfair: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/pepppper/roberta-unfair/resolve/main/training_args.bin
- Command line
-
hf download hf://pepppper/roberta-unfair/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pepppper/roberta-unfair/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 1341d1d91e77d918694c488dd508b57818bcb026a4f86362aefc4df715a5e716
- Size of remote file:
- 5.37 kB
- SHA256:
- c6f9534718e4097947339da11e70d18f4e9f0409c8046f80eab7ad5b91bea040
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