Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Sandrro/text_to_subfunction_v7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sandrro/text_to_subfunction_v7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sandrro/text_to_subfunction_v7")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sandrro/text_to_subfunction_v7") model = AutoModelForSequenceClassification.from_pretrained("Sandrro/text_to_subfunction_v7") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c62c668a4b6c4781a8521fa9b4b113c16e5c453c9318b99893482899bb302b70
- Size of remote file:
- 117 MB
- SHA256:
- b2ef096fe7bbc5c12a80112bb0fb25b6e7cd102aee41a58ccd8d8d326eb12582
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.