Text Ranking
Transformers
Safetensors
English
qwen2
text-generation
judge-model
evaluation
reward-modeling
Instructions to use opencompass/CompassJudger-2-32B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opencompass/CompassJudger-2-32B-Instruct with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("opencompass/CompassJudger-2-32B-Instruct") model = AutoModelForCausalLM.from_pretrained("opencompass/CompassJudger-2-32B-Instruct") - Notebooks
- Google Colab
- Kaggle
Add pipeline_tag, library_name, and paper link to metadata
#2
by nielsr HF Staff - opened
This PR enhances the model card by adding key metadata tags:
pipeline_tag: text-generation: This correctly categorizes the model, ensuring it appears in relevant searches and filters on the Hugging Face Hub (e.g., https://huggingface.co/models?pipeline_tag=text-generation).library_name: transformers: This indicates that the model can be easily loaded and used with the Hugging Face Transformers library, enabling the "Use in Transformers" widget on the model page for improved usability.paper: 2507.09104: This links the model directly to its official Hugging Face paper page, enhancing discoverability and providing immediate access to the research context.
The existing content of the model card is preserved as it already provides comprehensive information.
iridescentttt changed pull request status to merged