TIGER-Lab_MAmmoTH2-7B-GGUF

tensorblock/TIGER-Lab_MAmmoTH2-7B-GGUF

TIGER-Lab_MAmmoTH2-7B-GGUF is a machine learning model from tensorblock. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.

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Downloads · 30 days

2% of all-time downloads

All-time downloads

925

Public

Repo size

54.6 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.gguf2.7 GB · 100%

At a glance

Library: transformers
License: mit
Access: Public
Created: Apr 30, 2025
Updated: Jan 27, 2026
SHA: c1c6cd9a

Base models

TIGER-Lab/MAmmoTH2-7B

Datasets

TIGER-Lab/WebInstructSub

Model card

From the Hugging Face model README

TIGER-Lab/MAmmoTH2-7B - GGUF

This repo contains GGUF format model files for TIGER-Lab/MAmmoTH2-7B.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5165.

Our projects

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Prompt template

Model file specification

Filename	Quant type	File Size	Description
MAmmoTH2-7B-Q2_K.gguf	Q2_K	2.719 GB	smallest, significant quality loss - not recommended for most purposes
MAmmoTH2-7B-Q3_K_S.gguf	Q3_K_S	3.165 GB	very small, high quality loss
MAmmoTH2-7B-Q3_K_M.gguf	Q3_K_M	3.519 GB	very small, high quality loss
MAmmoTH2-7B-Q3_K_L.gguf	Q3_K_L	3.822 GB	small, substantial quality loss
MAmmoTH2-7B-Q4_0.gguf	Q4_0	4.109 GB	legacy; small, very high quality loss - prefer using Q3_K_M
MAmmoTH2-7B-Q4_K_S.gguf	Q4_K_S	4.140 GB	small, greater quality loss
MAmmoTH2-7B-Q4_K_M.gguf	Q4_K_M	4.368 GB	medium, balanced quality - recommended
MAmmoTH2-7B-Q5_0.gguf	Q5_0	4.998 GB	legacy; medium, balanced quality - prefer using Q4_K_M
MAmmoTH2-7B-Q5_K_S.gguf	Q5_K_S	4.998 GB	large, low quality loss - recommended
MAmmoTH2-7B-Q5_K_M.gguf	Q5_K_M	5.131 GB	large, very low quality loss - recommended
MAmmoTH2-7B-Q6_K.gguf	Q6_K	5.942 GB	very large, extremely low quality loss
MAmmoTH2-7B-Q8_0.gguf	Q8_0	7.696 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/TIGER-Lab_MAmmoTH2-7B-GGUF --include "MAmmoTH2-7B-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/TIGER-Lab_MAmmoTH2-7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

Library: transformers
License: mit
Languages: en
Created: Apr 30, 2025
Updated: Jan 27, 2026