Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use GioReg/bertdbmdzIhate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GioReg/bertdbmdzIhate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GioReg/bertdbmdzIhate")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GioReg/bertdbmdzIhate") model = AutoModelForSequenceClassification.from_pretrained("GioReg/bertdbmdzIhate", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd188a3f4873b53d70bb424c5a199bc2bee7a0f38276c00290b38a2f6971f09c
- Size of remote file:
- 443 MB
- SHA256:
- 0b7b28d7b4c214425f34d7468a557f6273e619f4fc16fc06b6e201ba2f9478d2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.