Update README.md

README.md

@@ -149,6 +149,30 @@ InverseCoder is a series of code LLMs instruction-tuned by generating data from
 | 7B  | [codellama/CodeLlama-7b-Python-hf](https://huggingface.co/codellama/CodeLlama-7b-Python-hf)          | [wyt2000/InverseCoder-CL-7B](https://huggingface.co/wyt2000/InverseCoder-CL-7B)                   | [wyt2000/InverseCoder-CL-7B-Evol-Instruct-90K](https://huggingface.co/datasets/wyt2000/InverseCoder-DS-6.7B-Evol-Instruct-90K)       |
 | 6.7B | [deepseek-ai/deepseek-coder-6.7b-base](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base) | [wyt2000/InverseCoder-DS-6.7B](https://huggingface.co/wyt2000/InverseCoder-DS-6.7B)               | [wyt2000/InverseCoder-DS-6.7B-Evol-Instruct-90K](https://huggingface.co/datasets/wyt2000/InverseCoder-DS-6.7B-Evol-Instruct-90K)     |
 
+## Usage
+
+Similar to [Magicoder-S-DS-6.7B](https://huggingface.co/ise-uiuc/Magicoder-S-DS-6.7B/), use the code below to get started with the model. Make sure you installed the [transformers](https://huggingface.co/docs/transformers/index) library.
+
+```python
+from transformers import pipeline
+import torch
+INVERSECODER_PROMPT = """You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.
+@@ Instruction
+{instruction}
+@@ Response
+"""
+instruction = <Your code instruction here>
+prompt = INVERSECODER_PROMPT.format(instruction=instruction)
+generator = pipeline(
+    model="wyt2000/InverseCoder-CL-7B",
+    task="text-generation",
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+result = generator(prompt, max_length=1024, num_return_sequences=1, temperature=0.0)
+print(result[0]["generated_text"])
+```
+
 ## Paper
 **Arxiv:** <https://arxiv.org/abs/2407.05700>
 
@@ -164,4 +188,11 @@ Please cite the paper if you use the models or datasets from InverseCoder.
       primaryClass={cs.CL},
       url={https://arxiv.org/abs/2407.05700}, 
 }
-```
+```
+
+## Acknowledgements
+
+* [Magicoder](https://github.com/ise-uiuc/magicoder): Training code, original dataset and data decontamination
+* [DeepSeek-Coder](https://github.com/deepseek-ai/DeepSeek-Coder): Base model for InverseCoder-DS
+* [CodeLlama](https://ai.meta.com/research/publications/code-llama-open-foundation-models-for-code/): Base model for InverseCoder-CL
+* [AutoMathText](https://github.com/yifanzhang-pro/AutoMathText): Self-evaluation and Data Selection method