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Felladrin/Llama-68M-Chat-v1 - GGUF

This repo contains GGUF format model files for Felladrin/Llama-68M-Chat-v1.

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

Prompt template

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename Quant type File Size Description
Llama-68M-Chat-v1-Q2_K.gguf Q2_K 0.033 GB smallest, significant quality loss - not recommended for most purposes
Llama-68M-Chat-v1-Q3_K_S.gguf Q3_K_S 0.037 GB very small, high quality loss
Llama-68M-Chat-v1-Q3_K_M.gguf Q3_K_M 0.038 GB very small, high quality loss
Llama-68M-Chat-v1-Q3_K_L.gguf Q3_K_L 0.039 GB small, substantial quality loss
Llama-68M-Chat-v1-Q4_0.gguf Q4_0 0.042 GB legacy; small, very high quality loss - prefer using Q3_K_M
Llama-68M-Chat-v1-Q4_K_S.gguf Q4_K_S 0.042 GB small, greater quality loss
Llama-68M-Chat-v1-Q4_K_M.gguf Q4_K_M 0.043 GB medium, balanced quality - recommended
Llama-68M-Chat-v1-Q5_0.gguf Q5_0 0.047 GB legacy; medium, balanced quality - prefer using Q4_K_M
Llama-68M-Chat-v1-Q5_K_S.gguf Q5_K_S 0.047 GB large, low quality loss - recommended
Llama-68M-Chat-v1-Q5_K_M.gguf Q5_K_M 0.048 GB large, very low quality loss - recommended
Llama-68M-Chat-v1-Q6_K.gguf Q6_K 0.053 GB very large, extremely low quality loss
Llama-68M-Chat-v1-Q8_0.gguf Q8_0 0.068 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-68M-Chat-v1-GGUF --include "Llama-68M-Chat-v1-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-68M-Chat-v1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
40
GGUF
Model size
68M 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-68M-Chat-v1-GGUF

Base model

JackFram/llama-68m
Quantized
(5)
this model

Datasets used to train tensorblock/Llama-68M-Chat-v1-GGUF

Evaluation results