Instructions to use DISLab/ReFeed-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DISLab/ReFeed-8B with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="DISLab/ReFeed-8B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DISLab/ReFeed-8B") model = AutoModelForCausalLM.from_pretrained("DISLab/ReFeed-8B") - Notebooks
- Google Colab
- Kaggle
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year={2025},
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url={https://openreview.net/forum?id=6BGDGKZN7q}
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year={2025},
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url={https://openreview.net/forum?id=6BGDGKZN7q}
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```
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## 🙏 Acknowledgement
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This research was supported by KISTI, and by the NRF. For GPU infrastructure, our work was supported by the IITP grant funded by MSIT.
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This work was supported by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (RS-2025-02653113, High-Performance Research AI Computing Infrastructure Support at the 2 PFLOPS Scale)
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