Instructions to use bradmin/rm_trl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bradmin/rm_trl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bradmin/rm_trl")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bradmin/rm_trl") model = AutoModelForSequenceClassification.from_pretrained("bradmin/rm_trl") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eab3fbb38934c838a54292639760179a3a6bcfba613372c2876d97ae34a29d27
- Size of remote file:
- 221 MB
- SHA256:
- 6d34785f2cee88be6dd9a1a1ec7f5d563d3ce4f66756fa6689dcd93360db10c0
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