Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use annS/roberta-base-prop-16-train-set with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use annS/roberta-base-prop-16-train-set with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="annS/roberta-base-prop-16-train-set")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("annS/roberta-base-prop-16-train-set") model = AutoModelForSequenceClassification.from_pretrained("annS/roberta-base-prop-16-train-set", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from annS/roberta-base-prop-16-train-set: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/annS/roberta-base-prop-16-train-set/resolve/main/training_args.bin
- Command line
-
hf download hf://annS/roberta-base-prop-16-train-set/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/annS/roberta-base-prop-16-train-set/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- 07deffae619bbf3f7879b5a7f4f3d0dc9edc9f8b941b850ff790be0cbfdd1531
- Size of remote file:
- 3.31 kB
- SHA256:
- e6b77e5f0d942f10b2adb0f606108a2130413a84d9da8b10e31d4a48b9e23f71
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