Instructions to use qingy2024/uigen-t3-8b-e1-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use qingy2024/uigen-t3-8b-e1-checkpoints with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen3-8B") model = PeftModel.from_pretrained(base_model, "qingy2024/uigen-t3-8b-e1-checkpoints") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use qingy2024/uigen-t3-8b-e1-checkpoints with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
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 qingy2024/uigen-t3-8b-e1-checkpoints to start chatting
Install Unsloth Studio (Windows)
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 qingy2024/uigen-t3-8b-e1-checkpoints to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for qingy2024/uigen-t3-8b-e1-checkpoints to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="qingy2024/uigen-t3-8b-e1-checkpoints", max_seq_length=2048, )
LoRA Checkpoint: Step 400
This is a LoRA (Low-Rank Adaptation) checkpoint for the model unsloth/Qwen3-8B.
It was saved at training step 400.
Training in progress... This checkpoint represents step 400 of 1326 total steps.
Progress: 400 out of 1326 steps
Training Details
This checkpoint was automatically uploaded during training.
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