Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use ltuzova/citation_intent_classification_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ltuzova/citation_intent_classification_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ltuzova/citation_intent_classification_roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ltuzova/citation_intent_classification_roberta") model = AutoModelForSequenceClassification.from_pretrained("ltuzova/citation_intent_classification_roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ltuzova/citation_intent_classification_roberta: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/ltuzova/citation_intent_classification_roberta/resolve/main/training_args.bin
- Command line
-
hf download hf://ltuzova/citation_intent_classification_roberta/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ltuzova/citation_intent_classification_roberta/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 2ef9cedddf0a29e831cbaf6ac6a75efd74997cd7c863a5803772f1047fd064b7
- Size of remote file:
- 4.03 kB
- SHA256:
- 3b7f58cffb7d70da6a2e292c5de3ee7838417a167d657e511574610d8ef27c17
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