Instructions to use havinash-ai/c5feaada-eb55-42bc-9402-2d6bf3824df4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/c5feaada-eb55-42bc-9402-2d6bf3824df4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2") model = PeftModel.from_pretrained(base_model, "havinash-ai/c5feaada-eb55-42bc-9402-2d6bf3824df4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f6d08b5d21481d7fab2cfb9ce426b112e109940f05fd0fa433768a6704b2a41
- Size of remote file:
- 6.78 kB
- SHA256:
- be1f5eabdd73441d20e89803b02548bc0728d2b0a784fd290d3ec036cbe939cd
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