Instructions to use Duckq/NLP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Duckq/NLP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Duckq/NLP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Duckq/NLP") model = AutoModelForSequenceClassification.from_pretrained("Duckq/NLP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d43fabf0745e49c49ee2b223c70dc17de71153a38378f287fe6e3233af4e59ee
- Size of remote file:
- 50.5 MB
- SHA256:
- c189c1126b82ecbd26d2e2c7aab8940e52b86a147dc2455afa5e5d26bcb4602b
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