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--- |
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language: |
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- en |
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tags: |
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- fluency |
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license: apache-2.0 |
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--- |
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This model represents an ONNX-optimized version of the original [parrot_fluency_model](https://huggingface.co/prithivida/parrot_fluency_model) model. |
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It has been specifically tailored for GPUs and may exhibit variations in performance when run on CPUs. |
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## Dependencies |
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Please install the following dependency before you begin working with the model: |
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```sh |
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pip install optimum[onnxruntime-gpu] |
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``` |
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## How to use |
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```python |
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from transformers import AutoTokenizer |
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from optimum.onnxruntime import ORTModelForSequenceClassification |
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from optimum.pipelines import pipeline |
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# load tokenizer and model weights |
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tokenizer = AutoTokenizer.from_pretrained('Deepchecks/parrot_fluency_model_onnx') |
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model = ORTModelForSequenceClassification.from_pretrained('Deepchecks/parrot_fluency_model_onnx') |
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# prepare the pipeline and generate inferences |
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user_inputs = ['Natural language processing is an interdisciplinary subfield of linguistics, computer science, and artificial intelligence.', |
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'Pass on what you have learned. Strength, mastery, hmm… but weakness, folly, failure, also. Yes, failure, most of all. The greatest teacher, failure is.', |
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'Whispering dreams, forgotten desires, chaotic thoughts, dance with words, meaning elusive, swirling amidst.'] |
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pip = pipeline(task='text-classification', model=model, tokenizer=tokenizer, device=device, accelerator="ort") |
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res = pip(user_inputs, batch_size=64, truncation="only_first") |
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``` |
