Instructions to use TechxGenus/Seed-Coder-8B-Instruct-DWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TechxGenus/Seed-Coder-8B-Instruct-DWQ 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("TechxGenus/Seed-Coder-8B-Instruct-DWQ") 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 TechxGenus/Seed-Coder-8B-Instruct-DWQ with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "TechxGenus/Seed-Coder-8B-Instruct-DWQ"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "TechxGenus/Seed-Coder-8B-Instruct-DWQ" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TechxGenus/Seed-Coder-8B-Instruct-DWQ", "messages": [ {"role": "user", "content": "Hello"} ] }'
| license: mit | |
| base_model: ByteDance-Seed/Seed-Coder-8B-Instruct | |
| pipeline_tag: text-generation | |
| library_name: mlx | |
| tags: | |
| - mlx | |
| # Seed-Coder-8B-Instruct-DWQ | |
| This model [Seed-Coder-8B-Instruct-DWQ](https://huggingface.co/TechxGenus/Seed-Coder-8B-Instruct-DWQ) was | |
| converted to MLX format from [Seed-Coder-8B-Instruct](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Instruct). | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("TechxGenus/Seed-Coder-8B-Instruct-DWQ") | |
| prompt = "write quick sort in python" | |
| if tokenizer.chat_template is not None: | |
| messages = [{"role": "user", "content": prompt}] | |
| prompt = tokenizer.apply_chat_template( | |
| messages, add_generation_prompt=True | |
| ) | |
| response = generate(model, tokenizer, prompt=prompt, verbose=True) | |
| ``` | |