Hugging Face Overview
Model Overview
2B_or_not_2B is a 2.5 billion parameter language model developed by SicariusSicariiStuff, fine-tuned from an original Google model. The model's name is a playful nod to invisietch and Shakespeare. It was fine-tuned on a laptop with a 4090 16GB GPU, taking approximately 4 hours.
Key Characteristics
- Parameter Count: 2.5 billion parameters.
- Censorship Level: Rated at 7.9 out of 10 (low to very low censorship), making it suitable for less restricted applications.
- Quantizations: Available in multiple quantized formats, including GGUFs (Static, iMatrix_GGUF-bartowski, iMatrix_GGUF-mradermacher), EXL2 (8.0-BIT down to 4.0-BIT), FP8, and Mobile (ARM) Q4_0_X_X.
Benchmarks
The model reports the following benchmark scores:
- Average: 6.55
- IFEval (0-Shot): 20.62
- BBH (3-Shot): 7.68
- MATH Lvl 5 (4-Shot): 1.74
- GPQA (0-shot): 0.00
- MuSR (0-shot): 4.85
- MMLU-PRO (5-shot): 4.43
Use Cases
This model is particularly suited for applications requiring a language model with a low censorship threshold. Its availability in various quantized formats makes it adaptable for deployment on different hardware, including mobile devices.