Text Classification
Transformers
PyTorch
English
distilbert
text-classfication
nlp
neural-compressor
PostTrainingsStatic
int8
Intel® Neural Compressor
text-embeddings-inference
Instructions to use Intel/distilbert-base-uncased-MRPC-int8-static-inc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/distilbert-base-uncased-MRPC-int8-static-inc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Intel/distilbert-base-uncased-MRPC-int8-static-inc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Intel/distilbert-base-uncased-MRPC-int8-static-inc") model = AutoModelForSequenceClassification.from_pretrained("Intel/distilbert-base-uncased-MRPC-int8-static-inc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e52a24c3535cc48139a526398f74bb1212228bd73de49684eb4513ea26414d3
- Size of remote file:
- 242 MB
- SHA256:
- 7a6878d13005de162d2c8416c3e7bb84f0e694b3f678cd3a87474be8bd588345
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