Instructions to use GGorman/DeepSeek-Coder-V2-Instruct-Q4-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use GGorman/DeepSeek-Coder-V2-Instruct-Q4-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir DeepSeek-Coder-V2-Instruct-Q4-mlx GGorman/DeepSeek-Coder-V2-Instruct-Q4-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
GGorman/DeepSeek-Coder-V2-Instruct-Q4-mlx
The Model GGorman/DeepSeek-Coder-V2-Instruct-Q4-mlx was converted to MLX format from deepseek-ai/DeepSeek-Coder-V2-Instruct using mlx-lm version 0.19.1.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("GGorman/DeepSeek-Coder-V2-Instruct-Q4-mlx")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
- Downloads last month
- 262
Model size
37B params
Tensor type
F16
·
U32 ·
Hardware compatibility
Log In to add your hardware
4-bit
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for GGorman/DeepSeek-Coder-V2-Instruct-Q4-mlx
Base model
deepseek-ai/DeepSeek-Coder-V2-Base Finetuned
deepseek-ai/DeepSeek-Coder-V2-Instruct