---
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):

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)