Instructions to use r2e-edits/deepswe-swebv-eval-n16-verifier-qwen3-lora64-agent-priority-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use r2e-edits/deepswe-swebv-eval-n16-verifier-qwen3-lora64-agent-priority-v1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-14B") model = PeftModel.from_pretrained(base_model, "r2e-edits/deepswe-swebv-eval-n16-verifier-qwen3-lora64-agent-priority-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7abd648774af686a18e1979cbaa78d31cec99c4c400acb7be0aa10cee7c52ae6
- Size of remote file:
- 514 MB
- SHA256:
- 2c009eb9cd3109e7a54c54efec23ff2394f38b8f64ff1233f9652ddfe2786691
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