metadata
license: apache-2.0
language:
- en
base_model:
- prithivMLmods/Lacaille-MoT-4B-Supreme2
pipeline_tag: text-generation
library_name: transformers
tags:
- text-generation-inference
- math
- code
- science
Lacaille-MoT-4B-Supreme2-GGUF
Lacaille-MoT-4B-Supreme2 is a high-efficiency, multi-domain model fine-tuned on Qwen3-4B using the Mixture of Thoughts (MoT) dataset enhanced with code, math, science expert clusters and an extended open code reasoning dataset. 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 File Table
| File Name | Size | Format | Description |
|---|---|---|---|
| Lacaille-MoT-4B-Supreme2.BF16.gguf | 8.05 GB | GGUF (BF16) | BFloat16 precision model file |
| Lacaille-MoT-4B-Supreme2.F16.gguf | 8.05 GB | GGUF (F16) | Float16 precision model file |
| Lacaille-MoT-4B-Supreme2.F32.gguf | 16.1 GB | GGUF (F32) | Float32 precision model file |
| Lacaille-MoT-4B-Supreme2.Q4_K_M.gguf | 2.5 GB | GGUF (Q4_K_M) | 4-bit quantized model file |
| Lacaille-MoT-4B-Supreme2.Q5_K_M.gguf | 2.89 GB | GGUF (Q5_K_M) | 5-bit quantized model file |
| Lacaille-MoT-4B-Supreme2.Q8_0.gguf | 4.28 GB | GGUF (Q8_0) | 8-bit quantized model file |
| config.json | 31 B | JSON | Configuration file |
| .gitattributes | 1.95 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):
