How to use hf-internal-testing/tiny-random-DebertaV2ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-DebertaV2ForSequenceClassification")
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForSequenceClassification", device_map="auto")
https://huggingface.co/hf-internal-testing/tiny-random-DebertaV2ForSequenceClassification/resolve/8be492d69a7ca8fee52febbc8cd5776cec5f6762/tokenizer.json
hf download hf://hf-internal-testing/tiny-random-DebertaV2ForSequenceClassification@8be492d69a7ca8fee52febbc8cd5776cec5f6762/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/hf-internal-testing/tiny-random-DebertaV2ForSequenceClassification/resolve/8be492d69a7ca8fee52febbc8cd5776cec5f6762/tokenizer.json
