Smol-Hub-tldr-GGUF

tensorblock/Smol-Hub-tldr-GGUF

Smol-Hub-tldr-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

0% of all-time downloads

All-time downloads

2.3K

Public

Repo size

3.3 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.gguf219 MB · 100%

At a glance

Library: transformers
License: mit
Access: Public
Created: Mar 21, 2025
Updated: Jan 27, 2026
SHA: 6b0e548e

Base models

davanstrien/Smol-Hub-tldr

Datasets

Model card

From the Hugging Face model README

davanstrien/Smol-Hub-tldr - GGUF

This repo contains GGUF format model files for davanstrien/Smol-Hub-tldr.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4882.

Our projects

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Model file specification

Filename	Quant type	File Size	Description
Smol-Hub-tldr-Q2_K.gguf	Q2_K	0.219 GB	smallest, significant quality loss - not recommended for most purposes
Smol-Hub-tldr-Q3_K_S.gguf	Q3_K_S	0.219 GB	very small, high quality loss
Smol-Hub-tldr-Q3_K_M.gguf	Q3_K_M	0.235 GB	very small, high quality loss
Smol-Hub-tldr-Q3_K_L.gguf	Q3_K_L	0.246 GB	small, substantial quality loss
Smol-Hub-tldr-Q4_0.gguf	Q4_0	0.229 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Smol-Hub-tldr-Q4_K_S.gguf	Q4_K_S	0.260 GB	small, greater quality loss
Smol-Hub-tldr-Q4_K_M.gguf	Q4_K_M	0.271 GB	medium, balanced quality - recommended
Smol-Hub-tldr-Q5_0.gguf	Q5_0	0.268 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Smol-Hub-tldr-Q5_K_S.gguf	Q5_K_S	0.283 GB	large, low quality loss - recommended
Smol-Hub-tldr-Q5_K_M.gguf	Q5_K_M	0.290 GB	large, very low quality loss - recommended
Smol-Hub-tldr-Q6_K.gguf	Q6_K	0.367 GB	very large, extremely low quality loss
Smol-Hub-tldr-Q8_0.gguf	Q8_0	0.386 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/Smol-Hub-tldr-GGUF --include "Smol-Hub-tldr-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/Smol-Hub-tldr-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

Library: transformers
License: mit
Created: Mar 21, 2025
Updated: Jan 27, 2026