Instructions to use Cournane/roberta-base-reduced-Lower_fabric with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-reduced-Lower_fabric with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-reduced-Lower_fabric")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-reduced-Lower_fabric") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-reduced-Lower_fabric", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09df3eb728ed99aa559c5a85f67488b5fd24d094382bfa82ba8ee0c6373cb42f
- Size of remote file:
- 3.9 kB
- SHA256:
- dee56064a1a146c64bd48ab83e3d4006215a4ce0df16150e7b64899352bd00d5
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