Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use HarikaR/German_intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HarikaR/German_intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HarikaR/German_intent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HarikaR/German_intent") model = AutoModelForSequenceClassification.from_pretrained("HarikaR/German_intent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ba852ad0c6937f377d5621a843c96998a3e8360c9136498f165385e20f53809
- Size of remote file:
- 4.92 kB
- SHA256:
- 9bdc088add1bf34d8fc7ddca405f812808deb2c801f9e1533de708c8cf571579
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.