tinylamma-20000-GGUF

tensorblock/tinylamma-20000-GGUF

tinylamma-20000-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. The card lists the license as apache-2.0.

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Downloads · 30 days

1% of all-time downloads

All-time downloads

727

Public

Repo size

8.4 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.gguf432 MB · 100%

At a glance

License: apache-2.0
Access: Public
Created: Dec 21, 2024
Updated: Jan 27, 2026
SHA: b5f42605

Base models

shitshow123/tinylamma-20000

Model card

From the Hugging Face model README

shitshow123/tinylamma-20000 - GGUF

This repo contains GGUF format model files for shitshow123/tinylamma-20000.

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

Our projects

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Model file specification

Filename	Quant type	File Size	Description
tinylamma-20000-Q2_K.gguf	Q2_K	0.432 GB	smallest, significant quality loss - not recommended for most purposes
tinylamma-20000-Q3_K_S.gguf	Q3_K_S	0.499 GB	very small, high quality loss
tinylamma-20000-Q3_K_M.gguf	Q3_K_M	0.548 GB	very small, high quality loss
tinylamma-20000-Q3_K_L.gguf	Q3_K_L	0.592 GB	small, substantial quality loss
tinylamma-20000-Q4_0.gguf	Q4_0	0.637 GB	legacy; small, very high quality loss - prefer using Q3_K_M
tinylamma-20000-Q4_K_S.gguf	Q4_K_S	0.640 GB	small, greater quality loss
tinylamma-20000-Q4_K_M.gguf	Q4_K_M	0.668 GB	medium, balanced quality - recommended
tinylamma-20000-Q5_0.gguf	Q5_0	0.766 GB	legacy; medium, balanced quality - prefer using Q4_K_M
tinylamma-20000-Q5_K_S.gguf	Q5_K_S	0.766 GB	large, low quality loss - recommended
tinylamma-20000-Q5_K_M.gguf	Q5_K_M	0.782 GB	large, very low quality loss - recommended
tinylamma-20000-Q6_K.gguf	Q6_K	0.903 GB	very large, extremely low quality loss
tinylamma-20000-Q8_0.gguf	Q8_0	1.170 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/tinylamma-20000-GGUF --include "tinylamma-20000-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/tinylamma-20000-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

License: apache-2.0
Created: Dec 21, 2024
Updated: Jan 27, 2026