Text Generation
MLX
Safetensors
English
phi
phi-2
html
css
web-development
code-generation
fine-tuned
apple-silicon
conversational
4-bit precision
Instructions to use nexsendev/webicoder-v3-mlx-q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use nexsendev/webicoder-v3-mlx-q4 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("nexsendev/webicoder-v3-mlx-q4") 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) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use nexsendev/webicoder-v3-mlx-q4 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "nexsendev/webicoder-v3-mlx-q4"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "nexsendev/webicoder-v3-mlx-q4" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nexsendev/webicoder-v3-mlx-q4", "messages": [ {"role": "user", "content": "Hello"} ] }'
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 50256, | |
| "eos_token_id": 50256, | |
| "do_sample": true, | |
| "temperature": 0.4, | |
| "top_p": 0.9, | |
| "top_k": 50, | |
| "repetition_penalty": 1.15, | |
| "max_new_tokens": 4096, | |
| "stop_strings": [ | |
| "</html>", | |
| "### Instruction:", | |
| "You are Deepcoder", | |
| "You are WebICoder" | |
| ], | |
| "transformers_version": "5.0.0" | |
| } |