--- library_name: transformers license: other license_name: tongyi-qianwen license_link: https://huggingface.co/Qwen/Qwen1.5-72B/blob/main/LICENSE base_model: Qwen/Qwen1.5-72B-Chat --- # Model Card for Model ID ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64c14f6b02e1f8f67c73bd05/pf4d6FA7DriRtVq5HCkxd.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64c14f6b02e1f8f67c73bd05/htflRMYp8ab8GfhP-lo-J.png) Introducing Smaug-2, the return of Smaug! This version of Smaug is based on the Qwen1.5-72B-Chat model and has undergone further fine-tuning. It is specialised in the areas of reasoning and coding. It outperforms Qwen1.5-72B-Chat on MT-Bench, as shown below. #### MT-Bench We ran MT-Bench with the Qwen conversation template. | Model | First Turn | Second Turn | Average | | ------| ---------- | ----------- | ------- | | Qwen1.5-72B-Chat | 8.59 | 8.08 | 8.34 | | Smaug-2-72B | 8.86 | 8.20 | 8.53 #### HumanEval We ran HumanEval with pass@1 with the Qwen conversation template. Smaug-2 outperforms Qwen1.5-72B-Chat by approximately 10%: | Model | pass@1 (%) | | ------| ---------- | | Qwen1.5-72B-Chat | 56.7 | | Smaug-2-72B | 66.5 | This version of Smaug uses new techniques and new data compared to [Smaug-72B](https://huggingface.co/abacusai/Smaug-72B-v0.1), and more information will be released later on. For now, see the previous Smaug paper: https://arxiv.org/abs/2402.13228. ## Model Details ### Model Sources [optional] - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses ### Direct Use [More Information Needed] ### Downstream Use [optional] [More Information Needed] ### Out-of-Scope Use [More Information Needed] ## Bias, Risks, and Limitations [More Information Needed] ### Recommendations Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data [More Information Needed] ### Training Procedure #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] #### Speeds, Sizes, Times [optional] [More Information Needed] ## Evaluation ### Testing Data, Factors & Metrics #### Testing Data [More Information Needed] #### Factors [More Information Needed] #### Metrics [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] [More Information Needed] ## Environmental Impact Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]