Instructions to use NiGuLa/google-bert_bert-base-multilingual-cased_ep10_lr1e-05_batchpergpu16_gpu1_weighted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NiGuLa/google-bert_bert-base-multilingual-cased_ep10_lr1e-05_batchpergpu16_gpu1_weighted with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NiGuLa/google-bert_bert-base-multilingual-cased_ep10_lr1e-05_batchpergpu16_gpu1_weighted")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NiGuLa/google-bert_bert-base-multilingual-cased_ep10_lr1e-05_batchpergpu16_gpu1_weighted") model = AutoModelForSequenceClassification.from_pretrained("NiGuLa/google-bert_bert-base-multilingual-cased_ep10_lr1e-05_batchpergpu16_gpu1_weighted") - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!