Instructions to use project-themis/Themis-RM-1.7B-PMP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use project-themis/Themis-RM-1.7B-PMP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="project-themis/Themis-RM-1.7B-PMP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("project-themis/Themis-RM-1.7B-PMP") model = AutoModelForSequenceClassification.from_pretrained("project-themis/Themis-RM-1.7B-PMP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a575e91cbbb1e79d3d5175959e74e1f334ba5e750cd69a8068ab3cfd42f99dfe
- Size of remote file:
- 1.91 GB
- SHA256:
- 572f40d072bf214e3fdf4fcc87620b7b3fa0cfb498ec10b5cb61dd9ea510084b
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