Instructions to use OpenAssistant/reward-model-electra-large-discriminator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenAssistant/reward-model-electra-large-discriminator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OpenAssistant/reward-model-electra-large-discriminator")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OpenAssistant/reward-model-electra-large-discriminator") model = AutoModelForSequenceClassification.from_pretrained("OpenAssistant/reward-model-electra-large-discriminator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6668a358908f76ab165a1db221173552e2555e502a6ee5e2fcdc20930c254506
- Size of remote file:
- 1.34 GB
- SHA256:
- 00fffef793100af475612223b133b0a85ad8acad886e8cf02a57348da1ab8b43
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