Instructions to use dimasik1987/7edb2adf-1ded-408b-9df4-36991c64fb3e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik1987/7edb2adf-1ded-408b-9df4-36991c64fb3e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "dimasik1987/7edb2adf-1ded-408b-9df4-36991c64fb3e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 292d2a31b3f82014bdcbfafc06f555c707bafcfa51b47f0025c5954275e88a0a
- Size of remote file:
- 6.71 kB
- SHA256:
- 6ad24935f9ca0e15f38ac2a48c9a53c3a2d918e7d48c610e89a71f2812729ba6
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