Instructions to use ApplauseLab/bankai-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ApplauseLab/bankai-v1 with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("ApplauseLab/bankai-v1") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use ApplauseLab/bankai-v1 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "ApplauseLab/bankai-v1" --prompt "Once upon a time"
- Atomic Chat
- Xet hash:
- 0b9d6073c09d863262739e9787bda234591d9afe9c2bb0f04b7914c7eeaf93e7
- Size of remote file:
- 11.4 MB
- SHA256:
- 66df3ea1d9a9f0b1c3e07b1620a33dfb0b3bf36b6ea4b1e52fe2fc1bd8da67d9
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