prithivMLmods/Qwen3-1.7B-ShiningValiant3-f32-GGUF
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Model: prithivMLmods/Qwen3-1.7B-ShiningValiant3-f32-GGUF
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2026-06-20 02:34:12 +08:00
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---
license: apache-2.0
language:
- en
base_model:
- ValiantLabs/Qwen3-1.7B-ShiningValiant3
pipeline_tag: text-generation
library_name: transformers
tags:
- text-generation-inference
---
# **Qwen3-1.7B-ShiningValiant3-f32-GGUF**
> Shining Valiant 3—available in Qwen3-1.7B, Qwen3-4B, and Qwen3-8B variants—is a specialized model focused on science, AI design, and general reasoning, built on the Qwen 3 architecture. It is fine-tuned on our latest high-difficulty science reasoning dataset generated with Deepseek R1 0528, leveraging AI to build better AI. This enhancement enables Shining Valiant 3 to assist in exploring cutting-edge innovations and improvements in AI. With improved general and creative reasoning, it excels in problem-solving and everyday conversational tasks. Its compact size ensures compatibility with local desktops, mobile devices, and ultra-fast server-side inference.
## Model Files
| File Name | Size | Quant Type |
|-----------|------|------------|
| Qwen3-1.7B-ShiningValiant3.F32.gguf | 6.89 GB | F32 |
| Qwen3-1.7B-ShiningValiant3.BF16.gguf | 3.45 GB | BF16 |
| Qwen3-1.7B-ShiningValiant3.F16.gguf | 3.45 GB | F16 |
| Qwen3-1.7B-ShiningValiant3.Q8_0.gguf | 1.83 GB | Q8_0 |
| Qwen3-1.7B-ShiningValiant3.Q6_K.gguf | 1.42 GB | Q6_K |
| Qwen3-1.7B-ShiningValiant3.Q5_K_M.gguf | 1.26 GB | Q5_K_M |
| Qwen3-1.7B-ShiningValiant3.Q5_K_S.gguf | 1.23 GB | Q5_K_S |
| Qwen3-1.7B-ShiningValiant3.Q4_K_M.gguf | 1.11 GB | Q4_K_M |
| Qwen3-1.7B-ShiningValiant3.Q4_K_S.gguf | 1.06 GB | Q4_K_S |
| Qwen3-1.7B-ShiningValiant3.Q3_K_L.gguf | 1 GB | Q3_K_L |
| Qwen3-1.7B-ShiningValiant3.Q3_K_M.gguf | 940 MB | Q3_K_M |
| Qwen3-1.7B-ShiningValiant3.Q3_K_S.gguf | 867 MB | Q3_K_S |
| Qwen3-1.7B-ShiningValiant3.Q2_K.gguf | 778 MB | Q2_K |
## 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):
![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

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{
"model_type": "qwen3"
}

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{"framework": "pytorch", "task": "others", "allow_remote": true}