---
base_model: Qwen/Qwen3.5-9B
library_name: peft
pipeline_tag: text-generation
tags:
- lora
- peft
- sft
- trl
- typst
- qwen3.5
private: true
---

# Qwen3.5 9B Typst SFT LoRA

This repository contains a PEFT LoRA adapter trained from `Qwen/Qwen3.5-9B`.
It does not include merged base-model weights.

## Contents

- `adapter_model.safetensors`: LoRA adapter weights
- `adapter_config.json`: PEFT adapter configuration
- `tokenizer.json`, `tokenizer_config.json`, `chat_template.jinja`: tokenizer sidecars from the training run

## Loading

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_model = "Qwen/Qwen3.5-9B"
adapter = "uam-rl/qwen35-9b-muon-lora-r16"

tokenizer = AutoTokenizer.from_pretrained(adapter)
model = AutoModelForCausalLM.from_pretrained(
    base_model,
    torch_dtype="auto",
    device_map="auto",
)
model = PeftModel.from_pretrained(model, adapter)
```

## Training

- Method: supervised fine-tuning with TRL `SFTTrainer`
- Adapter: LoRA, rank 16, alpha 32, dropout 0.05
- Optimizer: Muon
- Base model: `Qwen/Qwen3.5-9B`

The adapter was trained for internal evaluation on the Typst Universe scrape.