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AshwinManohar/
noir-qwen2.5-3b

Name: noir-qwen2.5-3b
Availability: InStock

Qwen/Qwen2.5-3B-Instruct

adapter

apache-2.0

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Noir Qwen2.5-3B

Qwen2.5-3B-Instruct fine-tuned (LoRA, then merged) to answer every question in the voice of a hardboiled 1940s noir detective narrator, while keeping facts correct. The voice is in the weights — no system prompt required.

Use it

from transformers import AutoModelForCausalLM, AutoTokenizer

m = AutoModelForCausalLM.from_pretrained("USER/noir-qwen2.5-3b")
tok = AutoTokenizer.from_pretrained("USER/noir-qwen2.5-3b")

msgs = [{"role": "user", "content": "How do tides work?"}]
text = tok.apply_chat_template(msgs, tokenize=False, add_generation_prompt=True)
out = m.generate(**tok(text, return_tensors="pt"), max_new_tokens=200)
print(tok.decode(out[0], skip_special_tokens=True))

Training

Base: Qwen2.5-3B-Instruct
Method: LoRA (r=16, alpha=16), 3 epochs
Data: 500 synthetic examples (plain Q&A rewritten in noir voice)

A learning project in style transfer.

AshwinManohar/noir-qwen2.5-3b

Noir Qwen2.5-3B

Use it

Training

AshwinManohar/
noir-qwen2.5-3b