Text Classification
Transformers
TensorBoard
Safetensors
gpt2
Generated from Trainer
trl
reward-trainer
Instructions to use blakenp/gpt-Reward with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blakenp/gpt-Reward with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="blakenp/gpt-Reward")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("blakenp/gpt-Reward") model = AutoModelForSequenceClassification.from_pretrained("blakenp/gpt-Reward", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 926e89e6f63dcf97320726adfe39590202f97f51bda583c4074a91f793c1affd
- Size of remote file:
- 5.37 kB
- SHA256:
- 52d638080db4d4de2728c9ccebf600cc18e08b8ada35ac7d18a70c0d8541d323
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