Downloads · 30 days
49
5% of all-time downloads
tensorblock/tini_llama_full-GGUF
tini_llama_full-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.
<div style="width: auto; margin-left: auto; margin-right: auto" <img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;" </div
Downloads · 30 days
49
5% of all-time downloads
All-time downloads
1.1K
Public
Repo size
9.4 GB
Likes
0
Public
Click a slice to open those files.
.gguf499 MB · 100%
From the Hugging Face model README
This repo contains GGUF format model files for AlexWortega/tini_llama_full.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| tini_llama_full-Q2_K.gguf | Q2_K | 0.499 GB | smallest, significant quality loss - not recommended for most purposes |
| tini_llama_full-Q3_K_S.gguf | Q3_K_S | 0.572 GB | very small, high quality loss |
| tini_llama_full-Q3_K_M.gguf | Q3_K_M | 0.622 GB | very small, high quality loss |
| tini_llama_full-Q3_K_L.gguf | Q3_K_L | 0.665 GB | small, substantial quality loss |
| tini_llama_full-Q4_0.gguf | Q4_0 | 0.718 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| tini_llama_full-Q4_K_S.gguf | Q4_K_S | 0.721 GB | small, greater quality loss |
| tini_llama_full-Q4_K_M.gguf | Q4_K_M | 0.749 GB | medium, balanced quality - recommended |
| tini_llama_full-Q5_0.gguf | Q5_0 | 0.854 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| tini_llama_full-Q5_K_S.gguf | Q5_K_S | 0.854 GB | large, low quality loss - recommended |
| tini_llama_full-Q5_K_M.gguf | Q5_K_M | 0.870 GB | large, very low quality loss - recommended |
| tini_llama_full-Q6_K.gguf | Q6_K | 0.999 GB | very large, extremely low quality loss |
| tini_llama_full-Q8_0.gguf | Q8_0 | 1.294 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/tini_llama_full-GGUF --include "tini_llama_full-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/tini_llama_full-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'