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kcxain
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Model Details
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kcxain
Model Tree
Qwen/Qwen2.5-Coder-7B-Instruct
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Output Modalities
Supported Functionality
KernelZero: Continual Co-Evolution of LLMs for Kernel Generation
The paper reports the following results with 10 sampled candidates per problem.
| Benchmark | pass@1 | pass@5 | pass@10 | fast_1@1 | fast_1@10 | fast_2@1 | fast_2@10 |
|---|---|---|---|---|---|---|---|
| Level 1 | 70.6 | 94.77 | 98.0 | 15.1 | 29.0 | 6.3 | 14.0 |
| Level 2 | 59.0 | 90.33 | 94.0 | 2.0 | 9.0 | 1.3 | 6.0 |
This checkpoint generates CUDA extensions from PyTorch modules. Use the KernelZero CUDA prompt and validation environment for reproducible evaluation.
python
from transformers import AutoModelForCausalLM, AutoTokenizer model_id = "kcxain/KernelZero-CUDA-SFT-7B"tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)model = AutoModelForCausalLM.from_pretrained( model_id, torch_dtype="auto", device_map="auto", trust_remote_code=True,)This release contains the merged Hugging Face inference weights from SFT checkpoint 3606. Optimizer states, scheduler state, RNG state, and distributed training artifacts are excluded.