Update README.md

README.md

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 **Aramis-2B-BitNet** *(2.41B params / Context Length: Maximum sequence length of 4096 tokens)*   
 A compact, agent-oriented small language model focused on language understanding and contextual decision-making.
 Built with an iterative post-training recipe: bilingual DPO (FR+EN) + model merging of FR-centric and EN-centric variants.
-Runs natively as BitNet 1.58-bit (ternary) and is available in GGUF 1.58-bit, lossless to the BF16 checkpoints.
+Runs natively as BitNet 1.58-bit (ternary) and is available in GGUF 1.58-bit, lossless to the BF16 checkpoint.
 
 **Why BitNet (and why this model)**    
 - BitNet b1.58 uses ternary weights (−1,0,+1) with abs-mean scaling : very low memory & energy, great CPU/edge throughput, unlike classic FP/INT SLMs. For more details on the underlying architecture and efficiency of BitNet, please refer to the official Microsoft Research publication: [BitNet b1.58 2B4T Technical Report](https://arxiv.org/abs/2504.12285)  
-- ModelStock7 demonstrates that a 2B BitNet can deliver SOTA language understanding in its class without sacrificing efficiency.
+- Aramis demonstrates that a 2B BitNet can deliver SOTA language understanding in its class without sacrificing efficiency.
 
 **Model Variants**