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 model.onnx from INC4AI/roberta-base-mrpc-int8-static-inc: direct link, hf CLI and curl.
- Browser
- Download file 308 MB
-
https://huggingface.co/INC4AI/roberta-base-mrpc-int8-static-inc/resolve/main/model.onnx
- Command line
-
hf download hf://INC4AI/roberta-base-mrpc-int8-static-inc/model.onnx
-
curl -L -o model.onnx https://huggingface.co/INC4AI/roberta-base-mrpc-int8-static-inc/resolve/main/model.onnx
308 MB
- Xet hash:
- 6ed3b8eeaff0c4dcc1a488226c9177c112b6f6dd2900d9577fb0a61a613e4820
- Size of remote file:
- 308 MB
- SHA256:
- 315f3dfad2e4344cfc4688634a4909c0505467bb3cec620509ad204af3662cea
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