How to use hf-internal-testing/tiny-random-DebertaV2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-DebertaV2Model")
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DebertaV2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-DebertaV2Model", device_map="auto")
https://huggingface.co/hf-internal-testing/tiny-random-DebertaV2Model/resolve/d5cefc727dff7d8cfd82a20b0a8fd2eaea184b1a/tokenizer.json
hf download hf://hf-internal-testing/tiny-random-DebertaV2Model@d5cefc727dff7d8cfd82a20b0a8fd2eaea184b1a/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/hf-internal-testing/tiny-random-DebertaV2Model/resolve/d5cefc727dff7d8cfd82a20b0a8fd2eaea184b1a/tokenizer.json
