cdreetz/kwen2.5-1.5b-v2

Triton Kernel Code Generation Model

This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct specialized for generating Triton GPU kernels.

Model Details

• Base Model: Qwen/Qwen2.5-1.5B-Instruct
• Fine-tuned on: 6000 examples of Triton kernel code from cdreetz/triton-sft-dataset-6k-v2

Usage

from transformers import AutoTokenizer, AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained("cdreetz/kwen2.5-1.5b-v2")
tokenizer = AutoTokenizer.from_pretrained("cdreetz/kwen2.5-1.5b-v2")

prompt = "Write a Triton kernel for element-wise addition:"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=512)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)

Limitations

• Specialized for Triton kernel generation only
• May require prompt engineering for optimal results
• Generated kernels should be tested before production use