Instructions to use SayBitekhan/7-gemma3-27b-uz-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SayBitekhan/7-gemma3-27b-uz-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-3-27b-it") model = PeftModel.from_pretrained(base_model, "SayBitekhan/7-gemma3-27b-uz-lora") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SayBitekhan/7-gemma3-27b-uz-lora: direct link, hf CLI and curl.
- Browser
- Download file 6.03 kB
-
https://huggingface.co/SayBitekhan/7-gemma3-27b-uz-lora/resolve/main/training_args.bin
- Command line
-
hf download hf://SayBitekhan/7-gemma3-27b-uz-lora/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SayBitekhan/7-gemma3-27b-uz-lora/resolve/main/training_args.bin
6.03 kB
- Xet hash:
- e7c6c56fe7c71a625e03c41453f4e6fc3550725f72c1a2421ca03e5ae4db699f
- Size of remote file:
- 6.03 kB
- SHA256:
- 80b6807b4e7ebd5789cfd15027666e49b302a1f9ec4f75c2b91a8b603e591de8
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