Instructions to use 2vhoc/lab21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 2vhoc/lab21 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-3B-bnb-4bit") model = PeftModel.from_pretrained(base_model, "2vhoc/lab21") - Notebooks
- Google Colab
- Kaggle
File size: 784 Bytes
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base_model: unsloth/Qwen2.5-3B-bnb-4bit
library_name: peft
pipeline_tag: text-generation
tags:
- lora
- qlora
- vietnamese
- lab21
license: apache-2.0
---
# Lab 21 — Qwen2.5-3B Vietnamese LoRA (r=16)
LoRA adapter fine-tuned on `5CD-AI/Vietnamese-alpaca-gpt4-gg-translated` (200 samples).
| Setting | Value |
|---------|-------|
| Base model | `unsloth/Qwen2.5-3B-bnb-4bit` |
| Rank / alpha | r=16, alpha=32 |
| Target modules | `q_proj`, `v_proj` |
| Eval perplexity | 4.55 |
| Student | Vũ Văn Học — 2A202600653 |
## Usage
```python
from peft import PeftModel
from unsloth import FastLanguageModel
base, tokenizer = FastLanguageModel.from_pretrained(
"unsloth/Qwen2.5-3B-bnb-4bit", load_in_4bit=True
)
model = PeftModel.from_pretrained(base, "2vhoc/lab21")
```
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