How to use CanisAI/teach-multilingual-gemma-4-e2b-r3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-4-e2b-it-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "CanisAI/teach-multilingual-gemma-4-e2b-r3")
How to use CanisAI/teach-multilingual-gemma-4-e2b-r3 with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for CanisAI/teach-multilingual-gemma-4-e2b-r3 to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for CanisAI/teach-multilingual-gemma-4-e2b-r3 to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for CanisAI/teach-multilingual-gemma-4-e2b-r3 to start chatting
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="CanisAI/teach-multilingual-gemma-4-e2b-r3", max_seq_length=2048, )
