MoritzLaurer HF staff commited on
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Update README.md

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@@ -16,7 +16,7 @@ datasets:
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  #pipeline_tag:
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  #- text-classification
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  widget:
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- - text: "I first thought that I really liked the movie, but upon second thought it was actually disappointing. [SEP] The movie was good."
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  model-index: # info: https://github.com/huggingface/hub-docs/blame/main/modelcard.md
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  - name: DeBERTa-v3-large-mnli-fever-anli-ling-wanli
@@ -115,7 +115,7 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
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  model = AutoModelForSequenceClassification.from_pretrained(model_name)
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  premise = "I first thought that I liked the movie, but upon second thought it was actually disappointing."
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- hypothesis = "The movie was good."
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  input = tokenizer(premise, hypothesis, truncation=True, return_tensors="pt")
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  output = model(input["input_ids"].to(device)) # device = "cuda:0" or "cpu"
 
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  #pipeline_tag:
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  #- text-classification
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  widget:
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+ - text: "I first thought that I really liked the movie, but upon second thought it was actually disappointing. [SEP] The movie was not good."
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  model-index: # info: https://github.com/huggingface/hub-docs/blame/main/modelcard.md
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  - name: DeBERTa-v3-large-mnli-fever-anli-ling-wanli
 
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  model = AutoModelForSequenceClassification.from_pretrained(model_name)
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  premise = "I first thought that I liked the movie, but upon second thought it was actually disappointing."
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+ hypothesis = "The movie was not good."
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  input = tokenizer(premise, hypothesis, truncation=True, return_tensors="pt")
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  output = model(input["input_ids"].to(device)) # device = "cuda:0" or "cpu"