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:
- 641f4a7c41ad804586313d0958150122710514406bc0b0279e97654aff54bcc3
- Size of remote file:
- 4.6 kB
- SHA256:
- cbd473640b089575e3b93f40caac6d96b1006088b463e865229fad92539da1e0
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