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Megatron-Bots-1.7B-Reasoning-GGUF
prithivMLmods/Megatron-Bots-1.7B-Reasoning-GGUF
Megatron-Bots-1.7B-Reasoning-GGUF is a text generation model from prithivMLmods. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
Megatron-Bots-1.7B-Reasoning is a logical reasoning and general-purpose thinking model fine-tuned from Qwen3-1.7B, specifically designed for advanced reasoning tasks and analytical problem-solving. Built with data ent…
All-time downloads
1.8K
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Repo size
25.3 GB
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0
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Repo makeup
Click a slice to open those files.
.gguf25.3 GB · 100%
At a glance
- Task
- Text Generation
- Library
- transformers
- License
- apache-2.0
- Model type
- qwen3
- Access
- Public
- Created
- Jun 8, 2025
- Updated
- Jun 9, 2025
- SHA
- c8e315a7
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Base models
Model card
From the Hugging Face model README
Megatron-Bots-1.7B-Reasoning-GGUF
Megatron-Bots-1.7B-Reasoning is a logical reasoning and general-purpose thinking model fine-tuned from Qwen3-1.7B, specifically designed for advanced reasoning tasks and analytical problem-solving. Built with data entries from the SynLogic Dataset, it excels at structured thinking, logical deduction, and comprehensive problem analysis in a compact yet powerful architecture.
Model Files
| File Name | Size | Format | Description |
|---|---|---|---|
| Megatron-Bots-1.7B-Reasoning.F32.gguf | 6.89 GB | F32 | Full precision 32-bit floating point |
| Megatron-Bots-1.7B-Reasoning.F16.gguf | 3.45 GB | F16 | Half precision 16-bit floating point |
| Megatron-Bots-1.7B-Reasoning.BF16.gguf | 3.45 GB | BF16 | Brain floating point 16-bit |
| Megatron-Bots-1.7B-Reasoning.Q8_0.gguf | 1.83 GB | Q8_0 | 8-bit quantized |
| Megatron-Bots-1.7B-Reasoning.Q6_K.gguf | 1.42 GB | Q6_K | 6-bit quantized |
| Megatron-Bots-1.7B-Reasoning.Q5_K_M.gguf | 1.26 GB | Q5_K_M | 5-bit quantized, medium quality |
| Megatron-Bots-1.7B-Reasoning.Q5_K_S.gguf | 1.23 GB | Q5_K_S | 5-bit quantized, small quality |
| Megatron-Bots-1.7B-Reasoning.Q4_K_M.gguf | 1.11 GB | Q4_K_M | 4-bit quantized, medium quality |
| Megatron-Bots-1.7B-Reasoning.Q4_K_S.gguf | 1.06 GB | Q4_K_S | 4-bit quantized, small quality |
| Megatron-Bots-1.7B-Reasoning.Q3_K_L.gguf | 1 GB | Q3_K_L | 3-bit quantized, large quality |
| Megatron-Bots-1.7B-Reasoning.Q3_K_M.gguf | 940 MB | Q3_K_M | 3-bit quantized, medium quality |
| Megatron-Bots-1.7B-Reasoning.Q3_K_S.gguf | 867 MB | Q3_K_S | 3-bit quantized, small quality |
| Megatron-Bots-1.7B-Reasoning.Q2_K.gguf | 778 MB | Q2_K | 2-bit quantized |
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):
- Task
- Text Generation
- Library
- transformers
- Type
- qwen3
- License
- apache-2.0
- Languages
- en
- Created
- Jun 8, 2025
- Updated
- Jun 9, 2025