Instructions to use havinash-ai/8a2cb479-c2de-4f1f-9d80-ef41fb2f5540 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/8a2cb479-c2de-4f1f-9d80-ef41fb2f5540 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-2b-it") model = PeftModel.from_pretrained(base_model, "havinash-ai/8a2cb479-c2de-4f1f-9d80-ef41fb2f5540") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd74f88b38e13974e51034424a6ddb0a8e9d7e745d1487fd4b3011faed02a770
- Size of remote file:
- 6.78 kB
- SHA256:
- 66b1f54b49c72f1c2635cbd5d5bb64f331b2aea5bf18845aacfc259d6cea4206
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