Vorenthos-r1

Fine-tuned version of deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B using Unsloth + QLoRA.

Training details

Setting	Value
Base model	deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
Fine-tuning method	QLoRA (r=16, alpha=16)
Precision (saved)	float16 (merged)
Max sequence length	2048
Batch size (effective)	8
Epochs	1
Learning rate	0.0002
Date trained	2026-07-26

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "vorenthiclabs/Vorenthos-r1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.float16,
    device_map="auto",
)

prompt = """<|User|>: Explain gradient descent in simple terms.
<|Assistant|>: <think>
"""

inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.6)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Prompt format

<|User|>: {your instruction here}
<|Assistant|>: <think>
{model chain-of-thought reasoning}
</think>
{final response}

License

MIT — see base model card for additional terms.