Text Generation
MLX
Safetensors
PEFT
English
phi3
mlx-lm
phi-3.5
lora
phishing
cybersecurity
conversational
custom_code
4-bit precision
Instructions to use rudycaz/phi35-phish-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use rudycaz/phi35-phish-mlx with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("rudycaz/phi35-phish-mlx") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - PEFT
How to use rudycaz/phi35-phish-mlx with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use rudycaz/phi35-phish-mlx with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "rudycaz/phi35-phish-mlx"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "rudycaz/phi35-phish-mlx" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rudycaz/phi35-phish-mlx", "messages": [ {"role": "user", "content": "Hello"} ] }'
- Xet hash:
- 49d863b71200415959623f4d1af238f4eace8e559ba2fe7517c78ec4e0542803
- Size of remote file:
- 12.6 MB
- SHA256:
- efd9264eb24b2ea2ac7dfaed3a15e2064698ea354b65cf0a96382f7c462a92e7
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