Instructions to use cunghoctienganh/06c7c383-04a5-496e-b993-9a58d9bc83a2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cunghoctienganh/06c7c383-04a5-496e-b993-9a58d9bc83a2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-135M") model = PeftModel.from_pretrained(base_model, "cunghoctienganh/06c7c383-04a5-496e-b993-9a58d9bc83a2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48fdde29a5f6e4317f5c6858c059531153bd5d9cd1ef007e8b3592c1621c7c79
- Size of remote file:
- 6.78 kB
- SHA256:
- 62478985fedfc94a3189da9e9c33a8e5d93626245306905431164b192ec48212
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