README.md

---
base_model: GSAI-ML/LLaDA-8B-Instruct
library_name: peft
pipeline_tag: text-generation
tags:
- adapter-transformers
- lora
- peft
- text-generation
- llada
---

# llada-instruct-void

LoRA adapter for
[`GSAI-ML/LLaDA-8B-Instruct`](https://huggingface.co/GSAI-ML/LLaDA-8B-Instruct).
This repository contains adapter weights only; load it together with the base
model.

## LoRA Config

- Rank: `32`
- Alpha: `64`
- Dropout: `0.05`
- Target modules: `q_proj`, `up_proj`, `ff_out`, `v_proj`, `ff_proj`, `k_proj`

## Usage

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

base_model_id = "GSAI-ML/LLaDA-8B-Instruct"
adapter_path = "akpon900/llada-instruct-void"

tokenizer = AutoTokenizer.from_pretrained(base_model_id, trust_remote_code=True)
base_model = AutoModelForCausalLM.from_pretrained(
    base_model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
    trust_remote_code=True,
)
model = PeftModel.from_pretrained(base_model, adapter_path)
model.eval()
```

## Notes

- Intended for research and experimentation.
- No benchmark results are included in this release.

## Framework Versions

- PEFT 0.17.1