Edit model card
TensorBlock

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

JackFram/llama-160m - GGUF

This repo contains GGUF format model files for JackFram/llama-160m.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template


Model file specification

Filename Quant type File Size Description
llama-160m-Q2_K.gguf Q2_K 0.066 GB smallest, significant quality loss - not recommended for most purposes
llama-160m-Q3_K_S.gguf Q3_K_S 0.075 GB very small, high quality loss
llama-160m-Q3_K_M.gguf Q3_K_M 0.080 GB very small, high quality loss
llama-160m-Q3_K_L.gguf Q3_K_L 0.085 GB small, substantial quality loss
llama-160m-Q4_0.gguf Q4_0 0.092 GB legacy; small, very high quality loss - prefer using Q3_K_M
llama-160m-Q4_K_S.gguf Q4_K_S 0.092 GB small, greater quality loss
llama-160m-Q4_K_M.gguf Q4_K_M 0.096 GB medium, balanced quality - recommended
llama-160m-Q5_0.gguf Q5_0 0.108 GB legacy; medium, balanced quality - prefer using Q4_K_M
llama-160m-Q5_K_S.gguf Q5_K_S 0.108 GB large, low quality loss - recommended
llama-160m-Q5_K_M.gguf Q5_K_M 0.110 GB large, very low quality loss - recommended
llama-160m-Q6_K.gguf Q6_K 0.125 GB very large, extremely low quality loss
llama-160m-Q8_0.gguf Q8_0 0.161 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/llama-160m-GGUF --include "llama-160m-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/llama-160m-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
172
GGUF
Model size
162M params
Architecture
llama

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference Examples
Unable to determine this model's library. Check the docs .

Model tree for tensorblock/llama-160m-GGUF

Quantized
(4)
this model

Dataset used to train tensorblock/llama-160m-GGUF