--- library_name: transformers language: - ru pipeline_tag: text-classification --- ### Model Description This model is a finely tuned version of padmajabfrl/Gender-Classification. The dataset consists of 26,000 lines. "loss": 0.0024 - **Developed by:** Tillicollaps - **Language(s) (NLP):** russian ## Uses from transformers import AutoTokenizer, AutoModelForSequenceClassification from transformers import TextClassificationPipeline, from transliterate import translit tokenizer = AutoTokenizer.from_pretrained("distilbert/distilbert-base-uncased") model = AutoModelForSequenceClassification.from_pretrained("CustomModel_Russia", num_labels=2) nlp = TextClassificationPipeline(model=model, tokenizer=tokenizer) #If the language of the text is different from English, use the 'translit' library. name = "Cтанислав" tran = translit(name, language_code='ru', reversed=True) result = nlp(tran) ### 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]