Instructions to use berkeley-nest/Starling-RM-7B-alpha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use berkeley-nest/Starling-RM-7B-alpha with Transformers:
# Load model directly from transformers import AutoTokenizer, LLMForSequenceRegression tokenizer = AutoTokenizer.from_pretrained("berkeley-nest/Starling-RM-7B-alpha") model = LLMForSequenceRegression.from_pretrained("berkeley-nest/Starling-RM-7B-alpha") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3bdf4845ea786db780312b0cf677f5b970b33218e89a7fe0270f2f6b330db89c
- Size of remote file:
- 5.31 kB
- SHA256:
- b0970cf0f8a8b2c721397d2b59e62220a6e0b2228225ba1537abeaf5fd367de8
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