Add library_name and pipeline_tag, correct license

README.md

@@ -1,6 +1,9 @@
 ---
 license: llama3
+library_name: transformers
+pipeline_tag: text-generation
 ---
+
 see our paper in https://arxiv.org/abs/2405.17743
 
 github repo: https://github.com/Cardinal-Operations/ORLM
@@ -31,7 +34,7 @@ Please replace the `{Question}` with any natural language OR question.
 Below is an operations research question. Build a mathematical model and corresponding python code using `coptpy` that appropriately addresses the question.
 
 # Question:
-A lab has 1000 units of medicinal ingredients to make two pills, a large pill and a small pill. A large pill requires 3 units of medicinal ingredients and 2 units of filler. A small pill requires 2 units of medicinal ingredients and 1 unit of filler. The lab has to make at least 100 large pills. However, since small pills are more popular at least 60% of the total number of pills must be small. How many of each should be made to minimize the total number of filler material needed?
+A lab has 1000 units of medicinal ingredients to make two pills, a large pill and a small pill. A large pill requires 3 units of medicinal ingredients and 2 units of filler. A large pill requires 3 units of medicinal ingredients and 2 units of filler. A small pill requires 2 units of medicinal ingredients and 1 unit of filler. The lab has to make at least 100 large pills. However, since small pills are more popular at least 60% of the total number of pills must be small. How many of each should be made to minimize the total number of filler material needed?
 
 # Response:
 --------------------------top-1 completion output by LLaMA-3-8B-ORLM under greedy decoding--------------------------
@@ -59,7 +62,7 @@ Using this model, we can apply linear programming techniques to find the optimal
 ## Python Code Solution Using `coptpy`:
 Here is a Python script using the `coptpy` library to solve the problem:
 
-\`\`\`python
+```python
 import coptpy as cp
 from coptpy import COPT
 
@@ -91,7 +94,7 @@ if model.status == COPT.OPTIMAL:
     print("Number of small pills to be made: {:.0f}".format(y.x))
 else:
     print("No optimal solution found.")
-\`\`\`
+```
 
 In this script, we first create a `COPT` environment and model. Then, we add two integer decision variables `x` and `y`, representing the number of large and small pills to be made, respectively.