Instructions to use aleegis10/1e54f794-0ef4-4e48-936e-f0367eab14a3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis10/1e54f794-0ef4-4e48-936e-f0367eab14a3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/tiny-random-LlamaForCausalLM") model = PeftModel.from_pretrained(base_model, "aleegis10/1e54f794-0ef4-4e48-936e-f0367eab14a3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93a2ce36f60abea43a2c9fc2e412b7b6425a877977e94c12303f09a4cd72a36f
- Size of remote file:
- 199 kB
- SHA256:
- 640eb665777249216cd238ecd5a966ae03c79ebce885fa30628aa6264313fd99
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