Instructions to use dongboklee/dPRM-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dongboklee/dPRM-14B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dongboklee/dPRM-14B")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dongboklee/dPRM-14B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78af695675c4fc8453e45a039d33450bec835340edcdac08f9a1af71f046ab0d
- Size of remote file:
- 11.4 MB
- SHA256:
- e20ddafc659ba90242154b55275402edeca0715e5dbb30f56815a4ce081f4893
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