Instructions to use ryota39/mluke-large-lite-reward with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ryota39/mluke-large-lite-reward with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ryota39/mluke-large-lite-reward")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ryota39/mluke-large-lite-reward") model = AutoModelForSequenceClassification.from_pretrained("ryota39/mluke-large-lite-reward") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a984c4e2a5d78ac5863a12606f779351523aea7c3c4c0681fd43bef027c89960
- Size of remote file:
- 5.11 kB
- SHA256:
- a9799ff210f5055dabed65609dc7ef3e3312661e0c97d4e61807999be20266d7
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