Instructions to use Cournane/roberta-base-labels-Lower_pattern with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-labels-Lower_pattern with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-labels-Lower_pattern")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-labels-Lower_pattern") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-labels-Lower_pattern", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Cournane/roberta-base-labels-Lower_pattern: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Cournane/roberta-base-labels-Lower_pattern/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Cournane/roberta-base-labels-Lower_pattern@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Cournane/roberta-base-labels-Lower_pattern/resolve/refs%2Fpr%2F1/pytorch_model.bin
499 MB
- Xet hash:
- 25f8d9fd532e703e0f370336946e3049254474c90b94af69332ae2e1360a9f8c
- Size of remote file:
- 499 MB
- SHA256:
- 48efc49dabdf70a74424fdcd8f59458a008b396475ec801463abfa185e67d54e
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