Text Classification
Transformers
PyTorch
ONNX
English
roberta
text-classfication
int8
Intel® Neural Compressor
neural-compressor
PostTrainingStatic
Eval Results (legacy)
text-embeddings-inference
Instructions to use INC4AI/roberta-base-mrpc-int8-static-inc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use INC4AI/roberta-base-mrpc-int8-static-inc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="INC4AI/roberta-base-mrpc-int8-static-inc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("INC4AI/roberta-base-mrpc-int8-static-inc") model = AutoModelForSequenceClassification.from_pretrained("INC4AI/roberta-base-mrpc-int8-static-inc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
6ba855c | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:40946530ea1bb6a7889d32b0aed23e9f2ba0a407fe9e68f20ccaf6269a45ea19
size 127033837
|