Zero-Shot Classification
Transformers
PyTorch
TensorFlow
ONNX
Safetensors
French
camembert
text-classification
sentence-similarity
nli
Instructions to use cmarkea/distilcamembert-base-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cmarkea/distilcamembert-base-nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="cmarkea/distilcamembert-base-nli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cmarkea/distilcamembert-base-nli") model = AutoModelForSequenceClassification.from_pretrained("cmarkea/distilcamembert-base-nli", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cbd81efae318390f5c1bcd74b26ef8ef3005495b64ac8cada81ea2e30121ddf1
- Size of remote file:
- 272 MB
- SHA256:
- 56f093082f760a8aee08eca70317c76ded72e6520efad1fd7e76412bc626c122
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.