Instructions to use zkjzou99/code-prm-critic-lora-32k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use zkjzou99/code-prm-critic-lora-32k with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("Qwen/Qwen3.5-4B") model = PeftModel.from_pretrained(base_model, "zkjzou99/code-prm-critic-lora-32k") - Transformers
How to use zkjzou99/code-prm-critic-lora-32k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zkjzou99/code-prm-critic-lora-32k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from zkjzou99/code-prm-critic-lora-32k: direct link, hf CLI and curl.
- Browser
- Download file 8.79 MB
-
https://huggingface.co/zkjzou99/code-prm-critic-lora-32k/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://zkjzou99/code-prm-critic-lora-32k/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/zkjzou99/code-prm-critic-lora-32k/resolve/main/adapter_model.safetensors
8.79 MB
- Xet hash:
- 6c6ab538249977edf03f8e9d7d2dcb2e2ee38d307ae5afa0f2649f6552dd67e1
- Size of remote file:
- 8.79 MB
- SHA256:
- 90458fc3aa482a5e2a84c57b84ed35b0b66fe3eb08981f06dd12f1202b16a582
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