Instructions to use Areepatw/mnli-trained-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Areepatw/mnli-trained-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Areepatw/mnli-trained-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Areepatw/mnli-trained-model") model = AutoModelForSequenceClassification.from_pretrained("Areepatw/mnli-trained-model") - Notebooks
- Google Colab
- Kaggle
Upload eval_results_BBMC_en_test.json with huggingface_hub
Browse files
eval_results_BBMC_en_test.json
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{"eval_loss": 1.041024088859558, "eval_model_preparation_time": 0.0037, "eval_accuracy": 0.4740518962075848, "eval_precision": 0.5480313588597411, "eval_recall": 0.4740518962075848, "eval_f1": 0.44582897815499706, "eval_runtime": 12.4009, "eval_samples_per_second": 404.002, "eval_steps_per_second": 50.561}
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