How to use hf-internal-testing/tiny-random-LayoutLMv2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-LayoutLMv2Model")
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-LayoutLMv2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-LayoutLMv2Model", device_map="auto")
https://huggingface.co/hf-internal-testing/tiny-random-LayoutLMv2Model/resolve/6a1b510769b344979a910a7d0bade613a9ec2dfc/tokenizer.json
hf download hf://hf-internal-testing/tiny-random-LayoutLMv2Model@6a1b510769b344979a910a7d0bade613a9ec2dfc/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/hf-internal-testing/tiny-random-LayoutLMv2Model/resolve/6a1b510769b344979a910a7d0bade613a9ec2dfc/tokenizer.json
