Instructions to use tk3879110/bert_finetuning_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tk3879110/bert_finetuning_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tk3879110/bert_finetuning_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tk3879110/bert_finetuning_test") model = AutoModelForSequenceClassification.from_pretrained("tk3879110/bert_finetuning_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval_results_mrpc.txt from tk3879110/bert_finetuning_test: direct link, hf CLI and curl.
- Browser
- Download file 139 Bytes
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https://huggingface.co/tk3879110/bert_finetuning_test/resolve/main/eval_results_mrpc.txt
- Command line
-
hf download hf://tk3879110/bert_finetuning_test/eval_results_mrpc.txt
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curl -L -o eval_results_mrpc.txt https://huggingface.co/tk3879110/bert_finetuning_test/resolve/main/eval_results_mrpc.txt
139 Bytes
| eval_loss = 0.46375401245028364 | |
| eval_acc = 0.8161764705882353 | |
| eval_f1 = 0.878048780487805 | |
| eval_acc_and_f1 = 0.8471126255380201 | |
| epoch = 1.0 | |