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kiel2/kiel-2-codex

sourceHugging Faceapache-2.0updated 11d agoView on Hugging Face
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Model Card

Kiel-2-Codex

Kiel-2-Codex is a specialized multimodal vision-language model fine-tuned on top of [Qwen/Qwen3-VL-4B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct). It bridges advanced visual perception with deep code generation, layout translation, and technical instruction-following.

To accommodate different hardware setups, this repository provides both quantized 4-bit weights and full 16-bit weights as separate directories, alongside the raw training adapter files.


Repository Structure

  • —`4bit/` — Pre-quantized 4-bit weights (ideal for lower VRAM setups like a Tesla T4 or consumer GPUs).
  • —`16bit/` — Full-precision 16-bit weights (ideal for high-VRAM training/inference).
  • —Root files — Contains the raw LoRA adapter weights (adapter_model.safetensors), tokenizer configuration, and chat template.

Quick Start (Python Inference)

You can easily load either version directly using Hugging Face transformers by specifying the appropriate subfolder:

Option A: Load the 4-bit Version (Recommended for standard GPUs)

python
import torch
from transformers import AutoModelForVision2Seq, AutoProcessor

model_id = "kiel2/kiel-2-codex"

print("Loading Kiel-2-Codex (4-bit)...")
model = AutoModelForVision2Seq.from_pretrained(
    model_id,
    subfolder="4bit",
    torch_dtype=torch.float16,
    device_map="auto"
)
processor = AutoProcessor.from_pretrained(model_id)
Option B: Load the 16-bit Version (Full Precision)
Python
import torch
from transformers import AutoModelForVision2Seq, AutoProcessor

model_id = "kiel2/kiel-2-codex"

print("Loading Kiel-2-Codex (16-bit)...")
model = AutoModelForVision2Seq.from_pretrained(
    model_id,
    subfolder="16bit",
    torch_dtype=torch.bfloat16 if torch.cuda.is_bf16_supported() else torch.float16,
    device_map="auto"
)
processor = AutoProcessor.from_pretrained(model_id)
Training Details

Base Model: Qwen/Qwen3-VL-4B-Instruct

Fine-Tuning Framework: Unsloth / Hugging Face TRL & PEFT

Task Focus: Multimodal code generation and structural layout analysis.

License

This model inherits the licensing structure of its base architecture under the Apache 2.0 License.