Instructions to use bradmin/reward-gpt-b6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bradmin/reward-gpt-b6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bradmin/reward-gpt-b6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bradmin/reward-gpt-b6") model = AutoModelForSequenceClassification.from_pretrained("bradmin/reward-gpt-b6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c25a8993c62aa08312dd8c45dc77a100ea8a15668d3fb386e3b5df395c268714
- Size of remote file:
- 5.08 GB
- SHA256:
- 3c177887f95b36a2b51b205a19065a54fe672a5b182394f0428060f09611d278
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