Model Card for LinalgZero-SFT-LoRA
The training code is available on Github.
This model is a fine-tuned version of Qwen/Qwen2.5-3B on the atomwalk12/linalgzero-sft dataset. It has been trained using TRL.
Quick start
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="atomwalk12/LinalgZero-SFT-LoRA", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
Training procedure
This model was trained with SFT.
Framework versions
- TRL: 0.20.0
- Transformers: 4.56.2
- Pytorch: 2.7.1
- Datasets: 4.4.1
- Tokenizers: 0.22.1
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# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rfvasile/LinalgZero-SFT-LoRA", device_map="auto")