Text Generation
PEFT
TensorBoard
Safetensors
English
unsloth
lora
qlora
vulnerability-detection
security
code-analysis
cybersecurity
ultival
adapter
conversational
Instructions to use starsofchance/Mistral-Unsloth-QLoRA-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use starsofchance/Mistral-Unsloth-QLoRA-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Ministral-8B-Instruct-2410") model = PeftModel.from_pretrained(base_model, "starsofchance/Mistral-Unsloth-QLoRA-adapter") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use starsofchance/Mistral-Unsloth-QLoRA-adapter 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 starsofchance/Mistral-Unsloth-QLoRA-adapter 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 starsofchance/Mistral-Unsloth-QLoRA-adapter to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for starsofchance/Mistral-Unsloth-QLoRA-adapter to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="starsofchance/Mistral-Unsloth-QLoRA-adapter", max_seq_length=2048, )
- Xet hash:
- 426dc1cdd22a5e439997e59147fc41befd6db4709e13d2d17da09fbf90e3a77e
- Size of remote file:
- 17.1 MB
- SHA256:
- d7edbeaf20dd7f571b5dd1c54d9ace4f9b6299127cc7ba2afb14a6d51a4a79a4
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