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
Download tokenizer.json from INC4AI/roberta-base-mrpc-int8-static-inc: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/INC4AI/roberta-base-mrpc-int8-static-inc/resolve/main/tokenizer.json
- Command line
-
hf download hf://INC4AI/roberta-base-mrpc-int8-static-inc/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/INC4AI/roberta-base-mrpc-int8-static-inc/resolve/main/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.