Instructions to use harman/gemma2-9b_ultrafeedback-qrandomized_neutrals_originalplusoursall_BT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harman/gemma2-9b_ultrafeedback-qrandomized_neutrals_originalplusoursall_BT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="harman/gemma2-9b_ultrafeedback-qrandomized_neutrals_originalplusoursall_BT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("harman/gemma2-9b_ultrafeedback-qrandomized_neutrals_originalplusoursall_BT") model = AutoModel.from_pretrained("harman/gemma2-9b_ultrafeedback-qrandomized_neutrals_originalplusoursall_BT", device_map="auto") - Notebooks
- Google Colab
- Kaggle