Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use JingLang/fine_tuned_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JingLang/fine_tuned_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JingLang/fine_tuned_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JingLang/fine_tuned_model") model = AutoModelForSequenceClassification.from_pretrained("JingLang/fine_tuned_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 150 Bytes
8cb1425 | 1 2 3 4 5 6 7 8 9 10 | {
"candidate_labels": [
"FACT",
"QUESTION",
"REQUEST",
"OPINION",
"COMPLAINT"
],
"hypothesis_template": "This text is {}."
} |