Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use MaVier19/zero-shot_text_classification_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MaVier19/zero-shot_text_classification_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MaVier19/zero-shot_text_classification_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MaVier19/zero-shot_text_classification_2") model = AutoModelForSequenceClassification.from_pretrained("MaVier19/zero-shot_text_classification_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0ffb7e43007264f100bd067bcfdc98901839c2a570d5cdbbc3fc1328c6d3800
- Size of remote file:
- 4.66 kB
- SHA256:
- 55cd16428abf53b6786530785badbad117cc1814e8221cc54b995fb32ea999fc
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