45 lines
1.9 KiB
Markdown
45 lines
1.9 KiB
Markdown
---
|
|
license: apache-2.0
|
|
datasets:
|
|
- prithivMLmods/Gargantua-R1-Wee
|
|
language:
|
|
- en
|
|
- zh
|
|
base_model:
|
|
- prithivMLmods/Gacrux-R1-Qwen3-1.7B-MoD
|
|
pipeline_tag: text-generation
|
|
library_name: transformers
|
|
tags:
|
|
- text-generation-inference
|
|
---
|
|
|
|
# **Gacrux-R1-Qwen3-1.7B-MoD-GGUF**
|
|
|
|
> Gacrux-R1-Qwen3-1.7B-MoD is a high-efficiency, multi-domain model fine-tuned on Qwen3-1.7B with traces of Mixture of Domains (MoD). It leverages the prithivMLmods/Gargantua-R1-Wee dataset, designed for rigorous mathematical problem-solving and enriched with multi-domain coverage across mathematics, coding, and science. This model blends symbolic precision, scientific logic, and structured output fluency—making it an ideal tool for developers, educators, and researchers seeking advanced reasoning under constrained compute.
|
|
|
|
## Model Files
|
|
|
|
| File Name | Quant Type | File Size |
|
|
| - | - | - |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.BF16.gguf | BF16 | 3.45 GB |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.F16.gguf | F16 | 3.45 GB |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.F32.gguf | F32 | 6.89 GB |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.Q2_K.gguf | Q2_K | 778 MB |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.Q3_K_L.gguf | Q3_K_L | 1 GB |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.Q3_K_M.gguf | Q3_K_M | 940 MB |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.Q3_K_S.gguf | Q3_K_S | 867 MB |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.Q4_K_M.gguf | Q4_K_M | 1.11 GB |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.Q4_K_S.gguf | Q4_K_S | 1.06 GB |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.Q5_K_M.gguf | Q5_K_M | 1.26 GB |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.Q5_K_S.gguf | Q5_K_S | 1.23 GB |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.Q6_K.gguf | Q6_K | 1.42 GB |
|
|
| Gacrux-R1-Qwen3-1.7B-MoD.Q8_0.gguf | Q8_0 | 1.83 GB |
|
|
|
|
## Quants Usage
|
|
|
|
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
|
|
|
|
Here is a handy graph by ikawrakow comparing some lower-quality quant
|
|
types (lower is better):
|
|
|
|
 |