tensorblock/typhoon-7b-instruct-02-19-2024-GGUF

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

scb10x/typhoon-7b-instruct-02-19-2024 - GGUF

This repo contains GGUF format model files for scb10x/typhoon-7b-instruct-02-19-2024.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Our projects

Awesome MCP Servers	TensorBlock 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

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename	Quant type	File Size	Description
typhoon-7b-instruct-02-19-2024-Q2_K.gguf	Q2_K	2.734 GB	smallest, significant quality loss - not recommended for most purposes
typhoon-7b-instruct-02-19-2024-Q3_K_S.gguf	Q3_K_S	3.181 GB	very small, high quality loss
typhoon-7b-instruct-02-19-2024-Q3_K_M.gguf	Q3_K_M	3.536 GB	very small, high quality loss
typhoon-7b-instruct-02-19-2024-Q3_K_L.gguf	Q3_K_L	3.839 GB	small, substantial quality loss
typhoon-7b-instruct-02-19-2024-Q4_0.gguf	Q4_0	4.127 GB	legacy; small, very high quality loss - prefer using Q3_K_M
typhoon-7b-instruct-02-19-2024-Q4_K_S.gguf	Q4_K_S	4.159 GB	small, greater quality loss
typhoon-7b-instruct-02-19-2024-Q4_K_M.gguf	Q4_K_M	4.387 GB	medium, balanced quality - recommended
typhoon-7b-instruct-02-19-2024-Q5_0.gguf	Q5_0	5.018 GB	legacy; medium, balanced quality - prefer using Q4_K_M
typhoon-7b-instruct-02-19-2024-Q5_K_S.gguf	Q5_K_S	5.018 GB	large, low quality loss - recommended
typhoon-7b-instruct-02-19-2024-Q5_K_M.gguf	Q5_K_M	5.151 GB	large, very low quality loss - recommended
typhoon-7b-instruct-02-19-2024-Q6_K.gguf	Q6_K	5.964 GB	very large, extremely low quality loss
typhoon-7b-instruct-02-19-2024-Q8_0.gguf	Q8_0	7.724 GB	very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/typhoon-7b-instruct-02-19-2024-GGUF --include "typhoon-7b-instruct-02-19-2024-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/typhoon-7b-instruct-02-19-2024-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'