How to use from the
Use from the
PEFT library
from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("ByteDance-Seed/Seed-Coder-8B-Instruct")
model = PeftModel.from_pretrained(base_model, "snsnc/Seed-Coder-8B-Instruct-Rust-Strandset-LoRA")

Seed-Coder-8B-Instruct Rust Strandset LoRA

LoRA adapter trained with Unsloth Studio on a 20k-row subset of Fortytwo-Network/Strandset-Rust-v1.

Base model:

ByteDance-Seed/Seed-Coder-8B-Instruct

Training data:

Fortytwo-Network/Strandset-Rust-v1

Mapping used:

  • input_data → user
  • output_data → assistant
  • task_category → system
  • crate_name → system
  • test → none

Training config:

  • Method: LoRA
  • Context: 4096
  • Epochs: 1
  • LR: 2e-4
  • Rank: 16
  • Alpha: 32
  • Dropout: 0.0
  • Batch size: 16
  • Grad accum: 2
  • Effective batch: 32
  • Weight decay: 0.001
  • Warmup steps: 25
  • Packing: off
  • Train on completions: on

Note: this adapter was trained on Strandset-style structured Rust code tasks. It may emit JSON-style wrappers such as {"code": "..."} depending on prompting.

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