2.0 KiB
2.0 KiB
license, language, base_model, pipeline_tag, library_name, tags
| license | language | base_model | pipeline_tag | library_name | tags | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| apache-2.0 |
|
|
text-generation | transformers |
|
Nenque-MoT-0.6B-Elite14-GGUF
Nenque-MoT-0.6B-Elite14 is a compact, high-efficiency model tailored for mathematical reasoning, code generation, and structured technical inference. Fine-tuned from Qwen3-0.6B using the MoT (Mixture of Thoughts) dataset—with a focus on math expert clusters—this model delivers strong symbolic performance in low-resource environments. Despite its 0.6B parameter size, it offers elite-level precision across STEM and multilingual technical domains.
Model File
| File Name | Size | Format | Description |
|---|---|---|---|
| Nenque-MoT-0.6B-Elite14.BF16.gguf | 1.2 GB | GGUF (BF16) | BFloat16 precision model file |
| Nenque-MoT-0.6B-Elite14.F16.gguf | 1.2 GB | GGUF (F16) | Float16 precision model file |
| Nenque-MoT-0.6B-Elite14.Q4_K_M.gguf | 397 MB | GGUF (Q4_K_M) | 4-bit quantized model file |
| Nenque-MoT-0.6B-Elite14.Q5_K_M.gguf | 444 MB | GGUF (Q5_K_M) | 5-bit quantized model file |
| unsloth.Q8_0.gguf | 639 MB | GGUF (Q8_0) | 8-bit quantized model file |
| config.json | 31 B | JSON | Configuration file |
| .gitattributes | 1.86 kB | Text | Git attributes configuration |
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):
