viplismism/deepseek-coder-6.7b-fim-reth-v1

deepseek-coder-6.7b-fim-reth-v1

A LoRA fine-tuned adapter for deepseek-ai/deepseek-coder-6.7b-base, specialized for Fill-in-the-Middle (FIM) code completion on the reth Rust codebase.

On a held-out reth test split it more than doubles the base model's exact-match rate (see Evaluation).

Want plug-and-play (Ollama / llama.cpp)? Use the GGUF build (q4km / q8_0) — no base model or PEFT needed.

Model Details

• —Base Model: deepseek-ai/deepseek-coder-6.7b-base
• —Fine-tuning Method: LoRA (Low-Rank Adaptation) with 4-bit quantization (QLoRA)
• —Training Data: AST-extracted FIM samples from the reth Rust codebase
• —Task: Fill-in-the-Middle code completion (predict missing code between prefix and suffix)

Training Configuration

FIM Format

Uses the DeepSeek Coder FIM token format:

<｜fim▁begin｜>[code before cursor]<｜fim▁hole｜>[code after cursor]<｜fim▁end｜>[generated completion]

Usage

from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

base = AutoModelForCausalLM.from_pretrained(
    "deepseek-ai/deepseek-coder-6.7b-base", device_map="auto", load_in_4bit=True)
model = PeftModel.from_pretrained(base, "viplismism/deepseek-coder-6.7b-fim-reth-v1")
tokenizer = AutoTokenizer.from_pretrained("viplismism/deepseek-coder-6.7b-fim-reth-v1")

prompt = "<｜fim▁begin｜>fn add(a: i32, b: i32) -> i32 {\n    <｜fim▁hole｜>\n}<｜fim▁end｜>"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=64, do_sample=False)
print(tokenizer.decode(out[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))

Evaluation

Evaluated on a held-out reth test split (200 samples never seen in training), tuned adapter vs. the unmodified base model, same FIM prompts:

The fine-tune wins on every metric. (pass@1 is strict exact-string match; edit-similarity/BLEU capture near-correct completions.)

Limitations

• —Tuned on Rust code from a single repository (reth) — generalizes less to other languages/repos.
• —FIM-only: expects the FIM prompt format above, not free-form chat.
• —Inherits the biases/limitations of deepseek-coder-6.7b-base.

License

Use of this adapter is subject to the DeepSeek License Agreement governing the base model.

Framework versions

• —transformers 4.49.0 · trl 0.17.0 · PEFT 0.19.1