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 tokenizer.json from SayBitekhan/7-gemma3-27b-uz-lora: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/SayBitekhan/7-gemma3-27b-uz-lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://SayBitekhan/7-gemma3-27b-uz-lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/SayBitekhan/7-gemma3-27b-uz-lora/resolve/main/tokenizer.json
33.4 MB
- Xet hash:
- fa66c8c017ade193f7cc37a2b421a1fc461563e803f179a496f7bdda2ec42c21
- Size of remote file:
- 33.4 MB
- SHA256:
- 4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.