Instructions to use OliverHeine/google_mobilebert-uncased_fold_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/google_mobilebert-uncased_fold_5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/google_mobilebert-uncased_fold_5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/google_mobilebert-uncased_fold_5") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/google_mobilebert-uncased_fold_5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c5d8c830dda9e968e378508fd8b1873c01df00a01cfb15f79766b1aeedfee36
- Size of remote file:
- 5.33 kB
- SHA256:
- 1db7af7d24bd7afdcd5cd3758e699b9f1ae21cb2aa629778aea53717b75658a9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.