SmolMaestra-1.7b-Translation Open-source Translation Model - Freely Achieve Effortless English-Italian Translation

Smolmaestra 1.7b Translation GGUF

Developed by tensorblock

SmolMaestra-1.7b-Translation is a 1.7B parameter translation model that supports translation tasks between English and Italian.

Machine Translation Supports Multiple LanguagesOpen Source License:Apache-2.0 #English-Italian Translation #Lightweight Model #Multiple Quantization Versions

Downloads 406

Release Time : 1/1/2025

Model Overview

This model focuses on translation tasks between English and Italian, providing multiple quantization versions in GGUF format suitable for different hardware environments.

Model Features

Multiple Quantization Versions

Offers 12 quantization versions from Q2_K to Q8_0 to meet different hardware performance and precision requirements

Lightweight Design

A relatively small model with 1.7B parameters, suitable for deployment in resource-limited environments

GGUF Format

Uses GGUF format, compatible with the latest version of llama.cpp for easy local deployment and usage

Model Capabilities

Bidirectional English-Italian translation

Text generation

Context understanding

Use Cases

Language Services

Document Translation

Translate English documents into Italian or vice versa

Fluid translation that maintains the semantic accuracy of the original text

Real-time Translation Service

Integrated into chat applications to provide real-time translation functionality

Low-latency conversational translation experience

Education

Language Learning Assistance

Help students understand foreign language texts

Provides accurate language conversion references

library_name: transformers base_model: puettmann/SmolMaestra-1.7b-Translation license: apache-2.0 language:

en
it tags:
translation
TensorBlock
GGUF

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puettmann/SmolMaestra-1.7b-Translation - GGUF

This repo contains GGUF format model files for puettmann/SmolMaestra-1.7b-Translation.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4823.

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## 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
SmolMaestra-1.7b-Translation-Q2_K.gguf	Q2_K	0.675 GB	smallest, significant quality loss - not recommended for most purposes
SmolMaestra-1.7b-Translation-Q3_K_S.gguf	Q3_K_S	0.777 GB	very small, high quality loss
SmolMaestra-1.7b-Translation-Q3_K_M.gguf	Q3_K_M	0.860 GB	very small, high quality loss
SmolMaestra-1.7b-Translation-Q3_K_L.gguf	Q3_K_L	0.933 GB	small, substantial quality loss
SmolMaestra-1.7b-Translation-Q4_0.gguf	Q4_0	0.991 GB	legacy; small, very high quality loss - prefer using Q3_K_M
SmolMaestra-1.7b-Translation-Q4_K_S.gguf	Q4_K_S	0.999 GB	small, greater quality loss
SmolMaestra-1.7b-Translation-Q4_K_M.gguf	Q4_K_M	1.056 GB	medium, balanced quality - recommended
SmolMaestra-1.7b-Translation-Q5_0.gguf	Q5_0	1.192 GB	legacy; medium, balanced quality - prefer using Q4_K_M
SmolMaestra-1.7b-Translation-Q5_K_S.gguf	Q5_K_S	1.192 GB	large, low quality loss - recommended
SmolMaestra-1.7b-Translation-Q5_K_M.gguf	Q5_K_M	1.225 GB	large, very low quality loss - recommended
SmolMaestra-1.7b-Translation-Q6_K.gguf	Q6_K	1.406 GB	very large, extremely low quality loss
SmolMaestra-1.7b-Translation-Q8_0.gguf	Q8_0	1.820 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/SmolMaestra-1.7b-Translation-GGUF --include "SmolMaestra-1.7b-Translation-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/SmolMaestra-1.7b-Translation-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

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