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:
- bcaecd49baab366c8348efc2238fdc8abe4bfb1fd243f0b2d8cc932288d8d11d
- Size of remote file:
- 4.97 GB
- SHA256:
- 36500ba655a8b9474cc0fb7d29da554c6ca95e14270254896023d858d9ae9979
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