Update README.md

README.md

@@ -12,7 +12,6 @@ SLAI T-Rex-Flash is an Operations Research (OR)–specialized model built from D
 - Paper: [SLAI T-Rex: Full-Parameter Post-training of the DeepSeek-V4 Family on Ascend SuperPOD](https://arxiv.org/abs/2607.20145)
 - Paper PDF: [arXiv:2607.20145](https://arxiv.org/pdf/2607.20145)
 - Code and training recipes: [SLAI-AITP/SLAI-T-Rex](https://github.com/SLAI-AITP/SLAI-T-Rex)
-- ModelScope weights: [SLAIAITP/DeepSeek-V4-Flash-OR](https://www.modelscope.cn/models/SLAIAITP/DeepSeek-V4-Flash-OR)
 
 ## Model Summary
 
@@ -80,18 +79,6 @@ The report also evaluates general-capability retention:
 
 Evaluation numbers should be compared only under the same prompt templates, decoding budgets, benchmark versions, solver environment, and scoring implementation described in the paper.
 
-## Limitations
-
-- Generated optimization models may be executable but mathematically incorrect; solver execution is not proof of structural equivalence.
-- The model can still make errors in variable domains, nonlinear expressions, ratios, quadratic terms, index alignment, and Gurobi-specific APIs.
-- Performance is strongest on the OR task families represented by the training and evaluation pipeline. Results may not transfer to unrelated domains or unseen solver ecosystems.
-- The reported results do not establish reliability for safety-critical, financial, medical, industrial, or legal decision making.
-- Always validate generated formulations, data interfaces, solver status, constraints, and objective values before use.
-
-## License
-
-Use of this checkpoint is governed by the license files and terms included in this repository. Users must also comply with any applicable terms of the DeepSeek-V4-Flash base checkpoint and third-party software such as Gurobi.
-
 ## Citation
 
 If you use this model, please cite the technical report: