starting the repo

README.md

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+![Quest Logo](logo.png)
+
+--------------------------------------------------------------------------------
+
+# QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation
+
+Paper: arxiv link goes here
+<!-- toc -->
+
+-----
+## <div align="center">Documentation</div>
+
+-----
+## <div align="center">Quick Start Examples</div>
+
+<details open>
+<summary>Install</summary>
+
+Install using pip (recommended):
+
+```bash
+pip install quest-decoding
+```
+
+</details>
+
+
+<details open>
+<summary>Length Reward</summary>
+
+Example using Length Reward
+
+```python
+
+    from langchain.prompts import PromptTemplate
+    from quest.model.vllm import VLLM
+    from quest.index import Uniform
+
+
+    template =  PromptTemplate.from_template(
+        "Translate this from {source_language} to {target_language}:\n{source_language}: {source_sentence}\n{target_language}:"
+    ) # a prompt template you define.
+
+    test_input_data = [{
+        "source_language": "English",
+        "target_language": "French",
+        "source_sentence": "Hello, how are you?"
+    }]
+
+    model = VLLM(
+        model_path="haoranxu/ALMA-7B",
+        prompt_template=template,
+        download_dir=os.environ["HF_HOME"],
+    )
+
+    reward = LengthReward() # a reward you define.
+
+    index = Uniform()
+
+    chain = Quest(
+        input_data=test_input_data,
+        model=model,
+        reward=reward,
+        dist=index,   
+    )
+
+    chain_outputs = chain.run(
+        steps=10,
+        use_tqdm=True,
+    )
+
+
+    print(chain_outputs.samples)
+
+```
+
+</details>
+
+
+-----
+
+## <div align="center">Contact</div>
+
+For bugs and feature requests please visit [GitHub Issues](https://github.com/goncalorafaria/quest-decoding/issues). For business inquiries or
+professional support requests please send an [e-mail]([email protected]).
+
+-----
+
+## <div align="center">Citation</div>
+
+````
+@inproceedings{
+    questdecoding,
+    title={QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation},
+    author={Gonçalo Faria, Sweta Agrawal, António Farinhas, Ricardo Rei, José G. C. de Souza, Andre Martins},
+    booktitle={},
+    year={2024},
+    url={arxiv link goes here}
+}
+````