ryzax_qwen3_1.7B_sft_correct_v3_1e-5_4-GGUF

tensorblock/ryzax_qwen3_1.7B_sft_correct_v3_1e-5_4-GGUF

ryzax_qwen3_1.7B_sft_correct_v3_1e-5_4-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. It is set up for transformers.

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Downloads · 30 days

2% of all-time downloads

All-time downloads

1.7K

Public

Repo size

16 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.gguf879 MB · 100%

At a glance

Library: transformers
Access: Public
Created: Aug 8, 2025
Updated: Jan 27, 2026
SHA: a47ad9b9

Base models

Model card

From the Hugging Face model README

ryzax/qwen3_1.7B_sft_correct_v3_1e-5_4 - GGUF

<div style="text-align: left; margin: 20px 0;"> <a href="https://discord.com/invite/Ej5NmeHFf2" style="display: inline-block; padding: 10px 20px; background-color: #5865F2; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;"> Join our Discord to learn more about what we're building ↗ </a> </div>

This repo contains GGUF format model files for ryzax/qwen3_1.7B_sft_correct_v3_1e-5_4.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5753.

Our projects

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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
qwen3_1.7B_sft_correct_v3_1e-5_4-Q2_K.gguf	Q2_K	0.879 GB	smallest, significant quality loss - not recommended for most purposes
qwen3_1.7B_sft_correct_v3_1e-5_4-Q3_K_S.gguf	Q3_K_S	1.000 GB	very small, high quality loss
qwen3_1.7B_sft_correct_v3_1e-5_4-Q3_K_M.gguf	Q3_K_M	1.073 GB	very small, high quality loss
qwen3_1.7B_sft_correct_v3_1e-5_4-Q3_K_L.gguf	Q3_K_L	1.137 GB	small, substantial quality loss
qwen3_1.7B_sft_correct_v3_1e-5_4-Q4_0.gguf	Q4_0	1.229 GB	legacy; small, very high quality loss - prefer using Q3_K_M
qwen3_1.7B_sft_correct_v3_1e-5_4-Q4_K_S.gguf	Q4_K_S	1.234 GB	small, greater quality loss
qwen3_1.7B_sft_correct_v3_1e-5_4-Q4_K_M.gguf	Q4_K_M	1.282 GB	medium, balanced quality - recommended
qwen3_1.7B_sft_correct_v3_1e-5_4-Q5_0.gguf	Q5_0	1.444 GB	legacy; medium, balanced quality - prefer using Q4_K_M
qwen3_1.7B_sft_correct_v3_1e-5_4-Q5_K_S.gguf	Q5_K_S	1.444 GB	large, low quality loss - recommended
qwen3_1.7B_sft_correct_v3_1e-5_4-Q5_K_M.gguf	Q5_K_M	1.471 GB	large, very low quality loss - recommended
qwen3_1.7B_sft_correct_v3_1e-5_4-Q6_K.gguf	Q6_K	1.672 GB	very large, extremely low quality loss
qwen3_1.7B_sft_correct_v3_1e-5_4-Q8_0.gguf	Q8_0	2.164 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/ryzax_qwen3_1.7B_sft_correct_v3_1e-5_4-GGUF --include "qwen3_1.7B_sft_correct_v3_1e-5_4-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/ryzax_qwen3_1.7B_sft_correct_v3_1e-5_4-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

Library: transformers
Created: Aug 8, 2025
Updated: Jan 27, 2026