Instructions to use maytemuma/merge_loraYbase_gemma_2_9b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use maytemuma/merge_loraYbase_gemma_2_9b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-9b") model = PeftModel.from_pretrained(base_model, "maytemuma/merge_loraYbase_gemma_2_9b") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from maytemuma/merge_loraYbase_gemma_2_9b: direct link, hf CLI and curl.
- Browser
- Download file 6.16 kB
-
https://huggingface.co/maytemuma/merge_loraYbase_gemma_2_9b/resolve/main/training_args.bin
- Command line
-
hf download hf://maytemuma/merge_loraYbase_gemma_2_9b/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/maytemuma/merge_loraYbase_gemma_2_9b/resolve/main/training_args.bin
6.16 kB
- Xet hash:
- 660747030630944ee86038fccf1b8cf4c5db7e608e5d4d70f5996f6556d46ab3
- Size of remote file:
- 6.16 kB
- SHA256:
- a763ddfd05325b02a702f5ec6fd203210a10c2a6c29caeaea675b524ff3cf2b8
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