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")# 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:
- 568e5955c792de6e365ba3917be429a5a48e94eefbdf43a3f46100b1f3713c31
- Size of remote file:
- 3.96 kB
- SHA256:
- cd8557a754b8f6dabb2f978e02626bf39e30336b76fa21281f5e3a6738a45a7c
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