Instructions to use OliverHeine/google_mobilebert-uncased_fold_8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/google_mobilebert-uncased_fold_8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/google_mobilebert-uncased_fold_8")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/google_mobilebert-uncased_fold_8") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/google_mobilebert-uncased_fold_8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from OliverHeine/google_mobilebert-uncased_fold_8: direct link, hf CLI and curl.
- Browser
- Download file 5.33 kB
-
https://huggingface.co/OliverHeine/google_mobilebert-uncased_fold_8/resolve/main/training_args.bin
- Command line
-
hf download hf://OliverHeine/google_mobilebert-uncased_fold_8/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/OliverHeine/google_mobilebert-uncased_fold_8/resolve/main/training_args.bin
5.33 kB
- Xet hash:
- 559cfbbe648464234c70c40ec5eaeb03f981bada59d1512fe7982bfaebee6121
- Size of remote file:
- 5.33 kB
- SHA256:
- a99fc0f6706b666a06f398b7613a577b8a5a53db6fb647d8ceb2f6c2828b23b7
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