How to use from
Unsloth StudioInstall 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 4rduino/training-Q8_0-GGUF to start chattingUsing HuggingFace Spaces for Unsloth
# No setup required# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for 4rduino/training-Q8_0-GGUF to start chattingLoad model with FastModel
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="4rduino/training-Q8_0-GGUF",
max_seq_length=2048,
)Quick Links
4rduino/training-Q8_0-GGUF
This LoRA adapter was converted to GGUF format from 4rduino/training via the ggml.ai's GGUF-my-lora space.
Refer to the original adapter repository for more details.
Use with llama.cpp
# with cli
llama-cli -m base_model.gguf --lora training-q8_0.gguf (...other args)
# with server
llama-server -m base_model.gguf --lora training-q8_0.gguf (...other args)
To know more about LoRA usage with llama.cpp server, refer to the llama.cpp server documentation.
- Downloads last month
- 5
Hardware compatibility
Log In to add your hardware
8-bit
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for 4rduino/training-Q8_0-GGUF
Base model
4rduino/training
Install Unsloth Studio (macOS, Linux, WSL)
# Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for 4rduino/training-Q8_0-GGUF to start chatting