Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Sandrro/text_to_function_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sandrro/text_to_function_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sandrro/text_to_function_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sandrro/text_to_function_v2") model = AutoModelForSequenceClassification.from_pretrained("Sandrro/text_to_function_v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 77d6c9d1d8fae56b18866ac1c6661aeaf8a1893ad9dec1ff82d68dfb2b31d06c
- Size of remote file:
- 117 MB
- SHA256:
- 53d9f5fcf4b519f6f6d5833bf5e0981efffb55f45d7e0daa431c3ee5edcf1093
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