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 pytorch_model.bin from annS/roberta-base-prop-16-train-set: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/annS/roberta-base-prop-16-train-set/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://annS/roberta-base-prop-16-train-set/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/annS/roberta-base-prop-16-train-set/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- b76fadb66fd9afa09273856c10966b520d102338b1b196a7a58b0ab035bdd042
- Size of remote file:
- 499 MB
- SHA256:
- ecfad2b306cf0f3278de1336f0491a6c8f2ab0d9a518a747362c298f3151f9db
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