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:
- ce5187dac15584a906293217fd2c4fd72fd3a45d1611bd654a6fb7d248aa8bdd
- Size of remote file:
- 166 MB
- SHA256:
- 3aac5acb92613688444d5d107643137014c1d2ee9e2ba78c43a8867f67cfeaca
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