Instructions to use amandaraeb/qs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amandaraeb/qs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amandaraeb/qs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amandaraeb/qs") model = AutoModelForSequenceClassification.from_pretrained("amandaraeb/qs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34e921239a6b3c31b6dff827ddb5012e5fb3cfe52995981d9593dbf19582d3af
- Size of remote file:
- 268 MB
- SHA256:
- e31d44eeeaa07bc1a51562af8168d71d6a710c2b76e3f0f268171e415d05c28f
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