nyu-mll/glue
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How to use echarlaix/distilbert-base-uncased-finetuned-sst-2-english-openvino with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="echarlaix/distilbert-base-uncased-finetuned-sst-2-english-openvino") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("echarlaix/distilbert-base-uncased-finetuned-sst-2-english-openvino")
model = AutoModelForSequenceClassification.from_pretrained("echarlaix/distilbert-base-uncased-finetuned-sst-2-english-openvino")Model Description: This model is a fine-tune checkpoint of DistilBERT-base-uncased, fine-tuned on SST-2. This model reaches an accuracy of 91.3 on the dev set.
You can use this model with Transformers pipeline.
from transformers import AutoTokenizer, pipeline
from optimum.intel.openvino import OVModelForSequenceClassification
model_id = "echarlaix/distilbert-base-uncased-finetuned-sst-2-english-openvino"
model = OVModelForSequenceClassification.from_pretrained(model_id)
tokenizer = AutoTokenizer.from_pretrained(model_id)
cls_pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
text = "He's a dreadful magician."
outputs = cls_pipe(text)