Add pipeline tag, code-translation tag, project page link and improve description

README.md

@@ -1,19 +1,22 @@
 ---
+base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
 library_name: transformers
 license: apache-2.0
-base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
 tags:
 - llama-factory
 - full
 - generated_from_trainer
+- code-translation
 model-index:
 - name: ex33_armv8
   results: []
+pipeline_tag: translation
 ---
 
 Check out more datails here:
 - Paper: https://arxiv.org/abs/2506.14606
 - Code: https://github.com/ahmedheakl/Guaranteed-Guess
+- Project page: https://ahmedheakl.github.io/Guaranteed-Guess/
   
 # ex33_armv8
 
@@ -21,15 +24,15 @@ This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-1.5B-Instruct](https:/
 
 ## Model description
 
-More information needed
+This model is part of the Guaranteed Guess (GG) pipeline, which tackles the challenging problem of CISC-to-RISC transpilation. GG combines the power of pre-trained large language models (LLMs) with software testing to generate and validate code translations between instruction set architectures (ISAs). This model is fine-tuned to translate from x86 (CISC) to ARMv8 (RISC).
 
 ## Intended uses & limitations
 
-More information needed
+This model is intended for researchers and developers interested in ISA transpilation, particularly CISC-to-RISC translation. It can be used to translate x86 assembly code to ARMv8 assembly code. However, the model's performance may vary depending on the complexity and optimization level of the input code.
 
 ## Training and evaluation data
 
-More information needed
+The model was trained and evaluated on the anghabench_armv8_O2_p1, the anghabench_armv8_O2_p2 and the stack_armv8_O2 datasets. These datasets include code snippets and programs designed to test the model's ability to translate between x86 and ARMv8 architectures.
 
 ## Training procedure
 
@@ -59,4 +62,4 @@ The following hyperparameters were used during training:
 - Transformers 4.50.0
 - Pytorch 2.6.0+cu124
 - Datasets 3.4.1
-- Tokenizers 0.21.0
+- Tokenizers 0.21.0