Instructions to use ravenluffy/RavenAI-CIPHER-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ravenluffy/RavenAI-CIPHER-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ravenluffy/RavenAI-CIPHER-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use ravenluffy/RavenAI-CIPHER-v2 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 ravenluffy/RavenAI-CIPHER-v2 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 ravenluffy/RavenAI-CIPHER-v2 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ravenluffy/RavenAI-CIPHER-v2 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="ravenluffy/RavenAI-CIPHER-v2", max_seq_length=2048, )
- Xet hash:
- c3cffe49b1659d49a6d4f3cfe63f73e96ff12bd5dcf6fd7d956d18c1c3ccf03e
- Size of remote file:
- 5.78 kB
- SHA256:
- 92a8284f99e4b4ed5fd7e38e6c295220ab1569d483adb98c28cb6c3366a84507
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