Instructions to use MikeDFT/devils-advocate-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MikeDFT/devils-advocate-adapter with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MikeDFT/devils-advocate-adapter", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use MikeDFT/devils-advocate-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 MikeDFT/devils-advocate-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 MikeDFT/devils-advocate-adapter to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MikeDFT/devils-advocate-adapter to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="MikeDFT/devils-advocate-adapter", max_seq_length=2048, )
| {% for message in messages %}{% if message['role'] == 'user' %}{{'<|im_start|>user | |
| ' + message['content'] + '<|im_end|> | |
| '}}{% elif message['role'] == 'assistant' %}{{'<|im_start|>assistant | |
| ' + message['content'] + '<|im_end|> | |
| ' }}{% else %}{{ '<|im_start|>system | |
| ' + message['content'] + '<|im_end|> | |
| ' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant | |
| ' }}{% endif %} |