Text Classification
Transformers
Safetensors
English
qwen3
code
reward-model
multilingual
text-embeddings-inference
Instructions to use project-themis/Themis-RM-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use project-themis/Themis-RM-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="project-themis/Themis-RM-4B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("project-themis/Themis-RM-4B") model = AutoModelForSequenceClassification.from_pretrained("project-themis/Themis-RM-4B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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[](https://huggingface.co/collections/project-themis/themis-reward-model-collection)
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[](https://huggingface.co/collections/project-themis/themis-preference-datasets-and-benchmarks)
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[](https://github.com/iNeil77/Themis)
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[](https://huggingface.co/collections/project-themis/themis-reward-model-collection)
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[](https://huggingface.co/collections/project-themis/themis-preference-datasets-and-benchmarks)
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[](https://github.com/iNeil77/Themis)
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[](https://hub.docker.com/repository/docker/ineil77/themis/general)
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