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:
- 99a164121909047536101a6e545fc2fd94bffc63b78a252b1f05fc33e3ebfa11
- Size of remote file:
- 5.08 GB
- SHA256:
- db3cf18dd827e5619410f288795d4376ad5b4706d678255b9891187b8cc03c72
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