| language: | |
| - en | |
| tags: | |
| - autotrain | |
| - text-classification | |
| datasets: | |
| - davanstrien/autotrain-data-dataset-mentions | |
| widget: | |
| - text: ' frases-bertimbau-v0.4 This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) | |
| on an unknown dataset.' | |
| - text: Model description BERTa is a transformer-based masked language model for the | |
| Catalan language. It is based on the [RoBERTA](https://github.com/pytorch/fairseq/tree/master/examples/roberta) | |
| base model and has been trained on a medium-size corpus collected from publicly | |
| available corpora and crawlers | |
| - text: Model description More information needed | |
| co2_eq_emissions: | |
| emissions: 0.008999666562870793 | |
| base_model: neuralmind/bert-base-portuguese-cased | |
| # Model Trained Using AutoTrain | |
| - Problem type: Binary Classification | |
| - Model ID: 3390592983 | |
| - CO2 Emissions (in grams): 0.0090 | |
| ## Validation Metrics | |
| - Loss: 0.014 | |
| - Accuracy: 0.997 | |
| - Precision: 0.998 | |
| - Recall: 0.997 | |
| - AUC: 1.000 | |
| - F1: 0.998 | |
| ## Usage | |
| You can use cURL to access this model: | |
| ``` | |
| $ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/davanstrien/autotrain-dataset-mentions-3390592983 | |
| ``` | |
| Or Python API: | |
| ``` | |
| from transformers import AutoModelForSequenceClassification, AutoTokenizer | |
| model = AutoModelForSequenceClassification.from_pretrained("davanstrien/autotrain-dataset-mentions-3390592983", use_auth_token=True) | |
| tokenizer = AutoTokenizer.from_pretrained("davanstrien/autotrain-dataset-mentions-3390592983", use_auth_token=True) | |
| inputs = tokenizer("I love AutoTrain", return_tensors="pt") | |
| outputs = model(**inputs) | |
| ``` |