metadata
license: apache-2.0
language:
- en
base_model:
- prithivMLmods/Eta-Aurigae-0.6B-Echelon1
pipeline_tag: text-generation
library_name: transformers
tags:
- text-generation-inference
- science
Eta-Aurigae-0.6B-Echelon1-GGUF
Eta-Aurigae-0.6B-Echelon1 is a compact, efficient model specialized in science, factual accuracy, and structured reasoning. Fine-tuned on Qwen3-0.6B using the MoT (Mixture of Thoughts) dataset—focused on scientific understanding and expert factual domains—it delivers high-precision outputs for STEM education, tutoring, and analytical thinking in resource-constrained environments.
Model File
| File Name | Size | Format | Description |
|---|---|---|---|
| Eta-Aurigae-0.6B-Echelon1.BF16.gguf | 1.2 GB | GGUF (BF16) | BFloat16 precision model file |
| Eta-Aurigae-0.6B-Echelon1.F32.gguf | 2.39 GB | GGUF (F32) | Float32 precision model file |
| Eta-Aurigae-0.6B-Echelon1.Q4_K_M.gguf | 397 MB | GGUF (Q4_K_M) | 4-bit quantized model file |
| Eta-Aurigae-0.6B-Echelon1.Q5_K_M.gguf | 444 MB | GGUF (Q5_K_M) | 5-bit quantized model file |
| Eta-Aurigae-0.6B-Echelon1.Q8_0.gguf | 639 MB | GGUF (Q8_0) | 8-bit quantized model file |
| config.json | 31 B | JSON | Configuration file |
| .gitattributes | 1.88 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):
