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 pytorch_model.bin from ltuzova/citation_intent_classification_roberta: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/ltuzova/citation_intent_classification_roberta/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ltuzova/citation_intent_classification_roberta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ltuzova/citation_intent_classification_roberta/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 07b9f91d111e16995186cbe94662aff626eac5f937c657c8286593b42598c61a
- Size of remote file:
- 499 MB
- SHA256:
- 7d076d24229c602e16c71c883f056078cb1ff31bb06c0f499fe108cea3272e23
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