--- library_name: transformers license: mit language: - en metrics: - bleu - code_eval - rouge - chrf model_name: MicroCoderFIM-1B base_model: bigcode/starcoderbase-1b model-index: - name: MicroCoderFIM-1B results: - task: type: text-generation dataset: type: openai_humaneval name: HumanEval metrics: - name: pass@1 type: pass@1 value: 65.46 verified: false - name: pass@10 type: pass@10 value: 90.36 verified: false - name: pass@100 type: pass@100 value: 94.43 verified: false - task: type: text-generation dataset: type: xvadov01/cpp_emb_nl2pl name: xvadov01/cpp_emb_nl2pl metrics: - name: BLEU type: bleu value: 31.74 verified: false - name: codeBLEU type: codeBLEU value: 40.53 verified: false - name: chrf++ type: chrf value: 51.54 verified: false - name: rouge-l type: rouge value: 43.31 verified: false --- # Model Card for Model ID This is a finetuned version of StarCoderBase 1B using the [Fill-in-the-Middle objective](https://arxiv.org/abs/2207.14255) on [dataset](https://huggingface.co/datasets/xvadov01/cpp_emb_nl2pl) focused on embedded systems programming. ## Model Details ### Model Description This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** Transformer decoder architecture with Multi-Query attention - **Language(s) (NLP):** English - **License:** MIT - **Finetuned from model [optional]:** [StarCoderBase 1B](https://huggingface.co/bigcode/starcoderbase-1b) ### 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:** NVIDIA GeForce RTX 3090 - **Hours used:** 5h 25m - **Carbon Emitted:** 0.83 ## 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]