Text Generation
PEFT
Safetensors
GGUF
English
qwen3
qwen3-8b
lora
code-style
android
kotlin
unsloth
qlora
llama-cpp
fine-tuning
conversational
Instructions to use antiableofnormies/qwen3-8b-lora-android-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use antiableofnormies/qwen3-8b-lora-android-dev with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen3-8b-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "antiableofnormies/qwen3-8b-lora-android-dev") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use antiableofnormies/qwen3-8b-lora-android-dev 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 antiableofnormies/qwen3-8b-lora-android-dev 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 antiableofnormies/qwen3-8b-lora-android-dev to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for antiableofnormies/qwen3-8b-lora-android-dev to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="antiableofnormies/qwen3-8b-lora-android-dev", max_seq_length=2048, )
File size: 133 Bytes
418612f | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:476870a1f2fb6f6a2759a6ede2383bf9d5d738f17844563b65c91965b722ae09
size 11422924
|