metadata
license: apache-2.0
base_model: Qwen/Qwen2.5-1.5B-Instruct
tags:
- triton
- kernel
- code-generation
- fine-tuned
datasets:
- cdreetz/triton-sft-dataset-6k-v2
language:
- en
pipeline_tag: text-generation
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