Text Classification
Transformers
English
qwen3
text-generation
llama-factory
full
Generated from Trainer
text-embeddings-inference
Instructions to use THU-KEG/DeepPrune-Judge-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use THU-KEG/DeepPrune-Judge-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="THU-KEG/DeepPrune-Judge-4B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("THU-KEG/DeepPrune-Judge-4B") model = AutoModelForCausalLM.from_pretrained("THU-KEG/DeepPrune-Judge-4B") - Notebooks
- Google Colab
- Kaggle
Update license metadata and add paper abstract
#1
by nielsr HF Staff - opened
This PR updates the model card for THU-KEG/DeepPrune-Judge-4B.
Key changes include:
- Updating the license in the metadata from
othertoapache-2.0, as found in the project's GitHub repository. - Adding the full paper abstract to provide a more comprehensive overview of the model.
- Removing the automatically generated boilerplate comment at the top of the model card.
tsq2000 changed pull request status to merged