Instructions to use beast33/92dd539b-2218-4565-9bb6-ce7dc3b376a1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/92dd539b-2218-4565-9bb6-ce7dc3b376a1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("zake7749/gemma-2-2b-it-chinese-kyara-dpo") model = PeftModel.from_pretrained(base_model, "beast33/92dd539b-2218-4565-9bb6-ce7dc3b376a1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b576019a9dc049af72d38a1d35f8086aadc3188608cfcd087a664796a22ad1c6
- Size of remote file:
- 6.84 kB
- SHA256:
- 896c7de491067ac4d78b7c97d1331a92ef25001992a9e8a471639c8bbec3b542
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