Create README.md

README.md

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+---
+license: apache-2.0
+datasets:
+- alexl83/AlpacaDataCleaned
+- sahil2801/CodeAlpaca-20k
+language:
+- en
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- rlhf
+- alignment
+- simulation
+- computational social science
+---
+
+
+# Model Card for So(cially)-Good LM
+
+![model image](https://agwarbliu.s3.amazonaws.com/logo.png)
+
+![model image](https://agwarbliu.s3.amazonaws.com/model_select_base.png)
+
+
+**Fast, Effective, and Stable alternative of RLHF!**
+
+**Instead of training an additional reward model that is likely to be gamed, we directly train the model on the social games!** 🕹️ 🎲 🎮
+
+Full details on simulation and training can be found [here](https://github.com/agi-templar/Stable-Alignment).
+
+# Training Procedure
+
+This is the very beginning of Stable Alignment project, which is an enhanced instruction tuning model based on LLaMA.
+
+We improve:
+
+- Instruction tuning data quality, by using [AlpacaDataCleaned](https://github.com/gururise/AlpacaDataCleaned), which fixes many errors in original Alpaca dataset.
+
+- Code pretraining with [codealpaca](https://github.com/sahil280114/codealpaca).
+
+We use the [Alpaca fine-tuning script](https://github.com/tatsu-lab/stanford_alpaca) to train this model.
+
+
+# Bias, Risks, and Limitations
+
+Although this project aims to better align current LMs with social norms, inappropriate content and inherent biases in the training data will still impair the alignment of the model.
+
+The model should not be used directly in any application, without a prior assessment of safety and fairness concerns specific to the application.