You can deploy this model and start earning money today!

tensorblock/
deepseek-coder-33b-instruct-GGUF

Name: deepseek-coder-33b-instruct-GGUF
Rating: 2.5 (142 reviews)

Views

No views yet

deepseek-ai/deepseek-coder-33b-instruct - GGUF

This repo contains GGUF format model files for deepseek-ai/deepseek-coder-33b-instruct.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Forge
Forge Project
An OpenAI-compatible multi-provider routing layer.
🚀 Try it now! 🚀
Awesome MCP Servers	TensorBlock Studio
MCP Servers	Studio
A comprehensive collection of Model Context Protocol (MCP) servers.	A lightweight, open, and extensible multi-LLM interaction studio.
👀 See what we built 👀	👀 See what we built 👀

## Prompt template

<｜begin▁of▁sentence｜>{system_prompt}### Instruction:
{prompt}
### Response:

Filename	Quant type	File Size	Description
deepseek-coder-33b-instruct-Q2_K.gguf	Q2_K	12.356 GB	smallest, significant quality loss - not recommended for most purposes
deepseek-coder-33b-instruct-Q3_K_S.gguf	Q3_K_S	14.422 GB	very small, high quality loss
deepseek-coder-33b-instruct-Q3_K_M.gguf	Q3_K_M	16.092 GB	very small, high quality loss
deepseek-coder-33b-instruct-Q3_K_L.gguf	Q3_K_L	17.560 GB	small, substantial quality loss
deepseek-coder-33b-instruct-Q4_0.gguf	Q4_0	18.819 GB	legacy; small, very high quality loss - prefer using Q3_K_M
deepseek-coder-33b-instruct-Q4_K_S.gguf	Q4_K_S	18.943 GB	small, greater quality loss
deepseek-coder-33b-instruct-Q4_K_M.gguf	Q4_K_M	19.941 GB	medium, balanced quality - recommended
deepseek-coder-33b-instruct-Q5_0.gguf	Q5_0	22.958 GB	legacy; medium, balanced quality - prefer using Q4_K_M
deepseek-coder-33b-instruct-Q5_K_S.gguf	Q5_K_S	22.958 GB	large, low quality loss - recommended
deepseek-coder-33b-instruct-Q5_K_M.gguf	Q5_K_M	23.536 GB	large, very low quality loss - recommended
deepseek-coder-33b-instruct-Q6_K.gguf	Q6_K	27.356 GB	very large, extremely low quality loss
deepseek-coder-33b-instruct-Q8_0.gguf	Q8_0	35.431 GB	very large, extremely low quality loss - not recommended

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/deepseek-coder-33b-instruct-GGUF --include "deepseek-coder-33b-instruct-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/deepseek-coder-33b-instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'