Instructions to use amiguel/SmolLM2-360M-concise-reasoning-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use amiguel/SmolLM2-360M-concise-reasoning-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceTB/SmolLM2-360M") model = PeftModel.from_pretrained(base_model, "amiguel/SmolLM2-360M-concise-reasoning-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a026bcdcb29ead51018e1169b48e27d2d0ef908d7ad5428258e881df03db3f42
- Size of remote file:
- 5.62 kB
- SHA256:
- 441b72c220fbe43338e5328907c054400cc31ee337ade07b95f2f7ea7d895c49
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