Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use namesarnav/counterbench-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use namesarnav/counterbench-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="namesarnav/counterbench-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("namesarnav/counterbench-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("namesarnav/counterbench-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from namesarnav/counterbench-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 5.33 kB
-
https://huggingface.co/namesarnav/counterbench-roberta-base/resolve/main/training_args.bin
- Command line
-
hf download hf://namesarnav/counterbench-roberta-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/namesarnav/counterbench-roberta-base/resolve/main/training_args.bin
5.33 kB
- Xet hash:
- c0566b0082c8f38f27b9fcb386a64ffde0f36c9b2609fd36d5f6d5a9c43265dd
- Size of remote file:
- 5.33 kB
- SHA256:
- 5c892534b5542c60e42ed536fec7d6fcdeca06f6b9a865873ce1d03a1c39c079
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