Instructions to use AngLv/NoisyRewards-in-RL-RM-acc-65 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AngLv/NoisyRewards-in-RL-RM-acc-65 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AngLv/NoisyRewards-in-RL-RM-acc-65")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AngLv/NoisyRewards-in-RL-RM-acc-65") model = AutoModelForSequenceClassification.from_pretrained("AngLv/NoisyRewards-in-RL-RM-acc-65", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0d3077fa2c2878ad86c38d1d0e0249ec30c311f01624f9ad75d83eb5b19da96
- Size of remote file:
- 7.29 kB
- SHA256:
- 7fe7e3207e38800fbf52a9c2ce6c29d1576e3d0191037dc26906852971f6d9d4
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