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metadata
license: apache-2.0
language:
  - en
base_model:
  - prithivMLmods/OpenRHO-2B-Thinker
pipeline_tag: text-generation
library_name: transformers
tags:
  - text-generation-inference

OpenRHO-2B-Thinker-GGUF

OpenRHO-2B-Thinker is a general-purpose reasoning model designed to enhance the cognitive abilities of edge-deployed large language models (LLMs) through reinforcement learning (RL). Fine-tuned from Qwen2-1.5B-Instruct using the QwQ distill dataset, it delivers refined improvements in logical reasoning, structured problem-solving, and lightweight coding — making it highly efficient for resource-constrained environments.

Model Files

File Name Size Quantization Format Description
OpenRHO-2B-Thinker.BF16.gguf 3.56 GB BF16 GGUF BFloat16 precision version
OpenRHO-2B-Thinker.F16.gguf 3.56 GB FP16 GGUF Float16 precision version
OpenRHO-2B-Thinker.F32.gguf 7.11 GB FP32 GGUF Float32 precision version
OpenRHO-2B-Thinker.Q2_K.gguf 753 MB Q2_K GGUF 2-bit quantized (K variant)
OpenRHO-2B-Thinker.Q3_K_M.gguf 924 MB Q3_K_M GGUF 3-bit quantized (K M variant)
OpenRHO-2B-Thinker.Q4_K_M.gguf 1.12 GB Q4_K_M GGUF 4-bit quantized (K M variant)
OpenRHO-2B-Thinker.Q4_K_S.gguf 1.07 GB Q4_K_S GGUF 4-bit quantized (K S variant)
OpenRHO-2B-Thinker.Q5_K_M.gguf 1.29 GB Q5_K_M GGUF 5-bit quantized (K M variant)
OpenRHO-2B-Thinker.Q5_K_S.gguf 1.26 GB Q5_K_S GGUF 5-bit quantized (K S variant)
OpenRHO-2B-Thinker.Q6_K.gguf 1.46 GB Q6_K GGUF 6-bit quantized (K variant)
OpenRHO-2B-Thinker.Q8_0.gguf 1.89 GB Q8_0 GGUF 8-bit quantized
.gitattributes 2.24 kB Git LFS tracking file
config.json 31 B Configuration file
README.md 670 B Model documentation

Quants Usage

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF Q2_K 0.4
GGUF Q3_K_S 0.5
GGUF Q3_K_M 0.5 lower quality
GGUF Q3_K_L 0.5
GGUF IQ4_XS 0.6
GGUF Q4_K_S 0.6 fast, recommended
GGUF Q4_K_M 0.6 fast, recommended
GGUF Q5_K_S 0.6
GGUF Q5_K_M 0.7
GGUF Q6_K 0.7 very good quality
GGUF Q8_0 0.9 fast, best quality
GGUF f16 1.6 16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png