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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51d2e80162db45bcdade35e3f6d368be7c5a90e0c9ba7ad0b8ee1abd9785b3f1
- Size of remote file:
- 5.08 GB
- SHA256:
- 01d1759e181163081c60769011571c86ceba9003064fd3ec598df9a98ae13224
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