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Update all references to canonical models (#29001)

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This commit is contained in:
Lysandre Debut
2024-02-16 08:16:58 +01:00
committed by GitHub
parent 1e402b957d
commit f497f564bb
561 changed files with 2682 additions and 2687 deletions
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docs/source/en/perf_infer_gpu_one.md
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@@ -348,7 +348,7 @@ ORT is supported by 🤗 Optimum which can be used in 🤗 Transformers. You'll
from optimum.onnxruntime import ORTModelForSequenceClassification
ort_model = ORTModelForSequenceClassification.from_pretrained(
"distilbert-base-uncased-finetuned-sst-2-english",
"distilbert/distilbert-base-uncased-finetuned-sst-2-english",
export=True,
provider="CUDAExecutionProvider",
)
@@ -360,7 +360,7 @@ Now you're free to use the model for inference:
from optimum.pipelines import pipeline
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english")
tokenizer = AutoTokenizer.from_pretrained("distilbert/distilbert-base-uncased-finetuned-sst-2-english")
pipeline = pipeline(task="text-classification", model=ort_model, tokenizer=tokenizer, device="cuda:0")
result = pipeline("Both the music and visual were astounding, not to mention the actors performance.")