fingpt-coder-1b5

LoRA adapter for Qwen/Qwen2.5-Coder-1.5B-Instruct fine-tuned on m-a-p/Code-Feedback (66K error→fix pairs, 3 epochs).

Adapter only — the base model is loaded from the HF Hub automatically. Total download: ~84 MB adapter + ~3 GB base model.

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LoRA config

Property	Value
Base model	Qwen/Qwen2.5-Coder-1.5B-Instruct
Rank (r)	16
Alpha	32 (scale = 2.0)
Target modules	q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
Training step	48500
Adapter size	~84 MB

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Quick start

git clone https://huggingface.co/revana/fingpt-coder-1b5

import torch, sys
sys.path.insert(0, "fingpt")          # fingpt repo root
from infer import load_model, generate

model, tokenizer = load_model("adapter_final.pt")

reply = generate(model, tokenizer, "Fix this bug:\n\ndef fact(n):\n    return n * fact(n)")
print(reply)

Or use the live demo.

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Training

Property	Value
Dataset	m-a-p/Code-Feedback
Samples	~66K error→fix pairs
Epochs	3
Batch size	4 × 4 grad accum = 16 effective
LR	3e-4, cosine decay, 3% warmup
Precision	bfloat16
Hardware	A100 80GB

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License

Apache 2.0