Instructions to use dzanbek/17da3748-dca8-4dc5-a3be-765dd02ff1a6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/17da3748-dca8-4dc5-a3be-765dd02ff1a6 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-1.7B") model = PeftModel.from_pretrained(base_model, "dzanbek/17da3748-dca8-4dc5-a3be-765dd02ff1a6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0fe53d888c4b51f26fc40ac6169479b9616436f62f2bc008218c94d2f8c073d
- Size of remote file:
- 72.5 MB
- SHA256:
- 9ff4bd78bfd526d99bf17a4e632a9aca2f85a1f17863f648548cee10afa0969e
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