Update README.md
Browse files
README.md
CHANGED
@@ -53,6 +53,27 @@ The models are evaluated using open-ended and multiple-choice math problems from
|
|
53 |
You can use the models through Huggingface's Transformers library. Use the pipeline function to create a text-generation pipeline with the model of your choice, then feed in a math problem to get the solution.
|
54 |
Check our Github repo for more advanced use: [https://github.com/TIGER-AI-Lab/MAmmoTH](https://github.com/TIGER-AI-Lab/MAmmoTH)
|
55 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
56 |
## Intended Uses
|
57 |
These models are trained for research purposes. They are designed to solve general math problems. They can be used in educational software, tutoring systems, or any application where a solution to a math problem is needed. The models can generate both a chain of thought (CoT) rationale and a program of thought (PoT) rationale, providing a comprehensive solution to a given math problem.
|
58 |
|
|
|
53 |
You can use the models through Huggingface's Transformers library. Use the pipeline function to create a text-generation pipeline with the model of your choice, then feed in a math problem to get the solution.
|
54 |
Check our Github repo for more advanced use: [https://github.com/TIGER-AI-Lab/MAmmoTH](https://github.com/TIGER-AI-Lab/MAmmoTH)
|
55 |
|
56 |
+
## Prompt Format
|
57 |
+
If you want to do CoT:
|
58 |
+
```
|
59 |
+
Below is an instruction that describes a task. Write a response that appropriately completes the request.
|
60 |
+
|
61 |
+
### Instruction:
|
62 |
+
{instruction}
|
63 |
+
|
64 |
+
### Response:
|
65 |
+
```
|
66 |
+
|
67 |
+
If you want to do PoT:
|
68 |
+
```
|
69 |
+
Below is an instruction that describes a task. Write a response that appropriately completes the request.
|
70 |
+
|
71 |
+
### Instruction:
|
72 |
+
{instruction} Let's write a program.
|
73 |
+
|
74 |
+
### Response:
|
75 |
+
```
|
76 |
+
|
77 |
## Intended Uses
|
78 |
These models are trained for research purposes. They are designed to solve general math problems. They can be used in educational software, tutoring systems, or any application where a solution to a math problem is needed. The models can generate both a chain of thought (CoT) rationale and a program of thought (PoT) rationale, providing a comprehensive solution to a given math problem.
|
79 |
|