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Model: prithivMLmods/Flerovium-Llama-3B-GGUF
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2026-09-16 17:37:17 +08:00
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---
library_name: transformers
tags:
- llama3.2
- math
- code
- text-generation-inference
license: apache-2.0
language:
- en
base_model:
- prithivMLmods/Flerovium-Llama-3B
pipeline_tag: text-generation
---
# **Flerovium-Llama-3B-GGUF**
> **Flerovium-Llama-3B** is a compact, general-purpose language model based on the powerful **llama 3.2** (llama) architecture. It is fine-tuned for a broad range of tasks including **mathematical reasoning**, **code generation**, and **natural language understanding**, making it a versatile choice for developers, students, and researchers seeking reliable performance in a lightweight model.
## Model File
| File Name | Size | Format |
|------------------------------------------|---------|--------|
| Flerovium-Llama-3B.BF16.gguf | 6.43 GB | BF16 |
| Flerovium-Llama-3B.F16.gguf | 6.43 GB | F16 |
| Flerovium-Llama-3B.Q4_K_M.gguf | 2.02 GB | Q4_K_M |
| Flerovium-Llama-3B.Q5_K_M.gguf | 2.32 GB | Q5_K_M |
| .gitattributes | 1.78 kB | - |
| README.md | 927 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}