Instructions to use mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-AWQ 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("mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-AWQ") 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 mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-AWQ with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-AWQ"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-AWQ" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-AWQ", "messages": [ {"role": "user", "content": "Hello"} ] }'
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README.md
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@@ -15,6 +15,8 @@ This model [mlx-community/deepseek-coder-v2-lite-instruct-4bit-awq](https://hugg
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converted to MLX format from [deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct](https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct)
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using mlx-lm version **0.25.2**.
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## Use with mlx
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```bash
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converted to MLX format from [deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct](https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct)
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using mlx-lm version **0.25.2**.
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AWQ Parameters: --bits 4 --group-size 64 --embed-bits 4 --embed-group-size 32 --num-samples 128 --sequence-length 1024 --n-grid 50 with a customized calibration dataset
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## Use with mlx
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```bash
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