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Model: prithivMLmods/Oganesson-TinyLlama-1.2B-GGUF
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2026-04-22 01:40:51 +08:00
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---
license: apache-2.0
language:
- en
base_model:
- prithivMLmods/Oganesson-TinyLlama-1.2B
pipeline_tag: text-generation
library_name: transformers
tags:
- text-generation-inference
- code
- math
- llama-3.2
---
# **Oganesson-TinyLlama-1.2B-GGUF**
> **Oganesson-TinyLlama-1.2B** is a lightweight and efficient language model built on the **LLaMA 3.2 1.2B** architecture. Fine-tuned for **general-purpose inference**, **mathematical reasoning**, and **code generation**, it’s ideal for edge devices, personal assistants, and educational applications requiring a compact yet capable model.
## Model File
| File Name | Size | Format |
|-----------------------------------------------|---------|--------|
| Oganesson-TinyLlama-1.2B.BF16.gguf | 2.48 GB | BF16 |
| Oganesson-TinyLlama-1.2B.F16.gguf | 2.48 GB | F16 |
| Oganesson-TinyLlama-1.2B.F32.gguf | 4.95 GB | F32 |
| Oganesson-TinyLlama-1.2B.Q4_K_M.gguf | 808 MB | Q4_K_M |
| .gitattributes | 1.8 kB | - |
| README.md | 212 B | - |
| config.json | 31 B | JSON |
## 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)

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{
"model_type": "llama"
}

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{"framework": "pytorch", "task": "others", "allow_remote": true}