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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.
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