Instructions to use aloxatel/W2L with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aloxatel/W2L with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aloxatel/W2L")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aloxatel/W2L") model = AutoModelForSequenceClassification.from_pretrained("aloxatel/W2L") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f915c0068f3c4355d058389d26fa7f9adcae3c59dd654fe0caabd6f832167d2
- Size of remote file:
- 1.42 GB
- SHA256:
- 4ebbdf82df2a0e097e51f1d93cd809505b855fbce0159ed25628417c2b8620bd
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