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Ahma-7B-GGUF

Text Generation
GGUF
Finnish
finnish
llama
TensorBlock
GGUF
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metadata
language:
  - fi
license: apache-2.0
tags:
  - finnish
  - llama
  - TensorBlock
  - GGUF
datasets:
  - Finnish-NLP/CulturaX_fi_cleaned
  - Finnish-NLP/HPLT_1.2_fi_cleaned
  - Finnish-NLP/wikipedia_20231101_fi_cleaned
  - Finnish-NLP/Reddit_fi_2006_2022
  - intfloat/multilingual_cc_news
inference: false
pipeline_tag: text-generation
base_model: Finnish-NLP/Ahma-7B
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Finnish-NLP/Ahma-7B - GGUF

This repo contains GGUF format model files for Finnish-NLP/Ahma-7B.

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

Prompt template 

<s> [INST] <<SYS>>
{system_prompt}
<</SYS>>

{prompt} [/INST]

Model file specification

Filename Quant type File Size Description
Ahma-7B-Q2_K.gguf Q2_K 2.685 GB smallest, significant quality loss - not recommended for most purposes
Ahma-7B-Q3_K_S.gguf Q3_K_S 3.114 GB very small, high quality loss
Ahma-7B-Q3_K_M.gguf Q3_K_M 3.464 GB very small, high quality loss
Ahma-7B-Q3_K_L.gguf Q3_K_L 3.763 GB small, substantial quality loss
Ahma-7B-Q4_0.gguf Q4_0 4.009 GB legacy; small, very high quality loss - prefer using Q3_K_M
Ahma-7B-Q4_K_S.gguf Q4_K_S 4.040 GB small, greater quality loss
Ahma-7B-Q4_K_M.gguf Q4_K_M 4.265 GB medium, balanced quality - recommended
Ahma-7B-Q5_0.gguf Q5_0 4.852 GB legacy; medium, balanced quality - prefer using Q4_K_M
Ahma-7B-Q5_K_S.gguf Q5_K_S 4.852 GB large, low quality loss - recommended
Ahma-7B-Q5_K_M.gguf Q5_K_M 4.983 GB large, very low quality loss - recommended
Ahma-7B-Q6_K.gguf Q6_K 5.747 GB very large, extremely low quality loss
Ahma-7B-Q8_0.gguf Q8_0 7.443 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/Ahma-7B-GGUF --include "Ahma-7B-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/Ahma-7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'