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
| 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") | |
| ``` | |