Instructions to use Cournane/roberta-base-labels-LowerClothingLength with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-labels-LowerClothingLength with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-labels-LowerClothingLength", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-labels-LowerClothingLength") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-labels-LowerClothingLength", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36b6812793c984ce47cd9449229917a4fcc51de92209076f0705846a65c6d5ef
- Size of remote file:
- 499 MB
- SHA256:
- 800007ef30335285578a4baa62a01dadb5284dc850d5fbf37ed73229e3706063
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