Instructions to use mousezhang/countdown-llada1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mousezhang/countdown-llada1.5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/testessfs10/users/zeyu.zhang/zk1/zkcopy/models/modelscope/LLaDA-1.5") model = PeftModel.from_pretrained(base_model, "mousezhang/countdown-llada1.5") - Notebooks
- Google Colab
- Kaggle
| base_model: GSAI-ML/LLaDA-1.5 | |
| tags: | |
| - lora | |
| - peft | |
| - countdown | |
| # COUNTDOWN LoRA Adapter for LLaDA-1.5 | |
| This is a LoRA adapter fine-tuned on **GSAI-ML/LLaDA-1.5** for the **countdown** task. | |
| ## Usage | |
| ```python | |
| from peft import PeftModel | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| # 加载基座模型 | |
| base_model = AutoModelForCausalLM.from_pretrained("GSAI-ML/LLaDA-1.5") | |
| tokenizer = AutoTokenizer.from_pretrained("GSAI-ML/LLaDA-1.5") | |
| # 加载 adapter | |
| model = PeftModel.from_pretrained(base_model, "mousezhang/countdown-llada1.5") | |
| ``` | |
| ## Training Config | |
| - **Base Model**: GSAI-ML/LLaDA-1.5 | |
| - **Task**: countdown | |
| - **LoRA Rank**: 128 | |
| - **LoRA Alpha**: 64 | |
| - **Target Modules**: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj | |