Instructions to use 0xsoftboi/gemma-4-e2b-it-kali-nethunter-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use 0xsoftboi/gemma-4-e2b-it-kali-nethunter-lora 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("0xsoftboi/gemma-4-e2b-it-kali-nethunter-lora") 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 0xsoftboi/gemma-4-e2b-it-kali-nethunter-lora with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "0xsoftboi/gemma-4-e2b-it-kali-nethunter-lora" --prompt "Once upon a time"
- Xet hash:
- f2571e5a2ebc185063917cb32d857665517ecbd393c33d7d692aa03267a7d44e
- Size of remote file:
- 7.3 MB
- SHA256:
- 47e5c48630875584e1d5d368beac7747e64c35a227477024c59a71bcf55db82f
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