Instructions to use project-themis/Themis-RM-4B-PMP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use project-themis/Themis-RM-4B-PMP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="project-themis/Themis-RM-4B-PMP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("project-themis/Themis-RM-4B-PMP") model = AutoModelForSequenceClassification.from_pretrained("project-themis/Themis-RM-4B-PMP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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library_name: transformers
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license: apache-2.0
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datasets:
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- Skywork/Skywork-Reward-Preference-80K-v0.2
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- allenai/tulu-3-pref-personas-instruction-following
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- allenai/preference-datasets-tulu
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- lmarena-ai/arena-human-preference-140k
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- prometheus-eval/Preference-Collection
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- nvidia/HelpSteer3
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- argilla/distilabel-math-preference-dpo
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- jondurbin/truthy-dpo-v0.1
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base_model:
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- Qwen/Qwen3-4B
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pipeline_tag: text-classification
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library_name: transformers
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license: apache-2.0
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datasets:
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- project-themis/Themis-GeneralPreference
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base_model:
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- Qwen/Qwen3-4B
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pipeline_tag: text-classification
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