Instructions to use ai-shift/sample-model-rm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ai-shift/sample-model-rm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ai-shift/sample-model-rm")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ai-shift/sample-model-rm") model = AutoModelForSequenceClassification.from_pretrained("ai-shift/sample-model-rm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ed252c73ec34915a466daa8d9018a1c25f8de0e2a313ffdbde53ca2511b0e0e
- Size of remote file:
- 500 MB
- SHA256:
- 2a18d098aa70f569ae5dbc95fc715f412a3e8c0175a0cb1c9650df2cd36b4dc7
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