How to use hf-tiny-model-private/tiny-random-MarkupLMModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-MarkupLMModel")
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MarkupLMModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MarkupLMModel", device_map="auto")
https://huggingface.co/hf-tiny-model-private/tiny-random-MarkupLMModel/resolve/b8b129806ea7d1b1149ffb8b8f7ffebbf75ea405/tokenizer.json
hf download hf://hf-tiny-model-private/tiny-random-MarkupLMModel@b8b129806ea7d1b1149ffb8b8f7ffebbf75ea405/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/hf-tiny-model-private/tiny-random-MarkupLMModel/resolve/b8b129806ea7d1b1149ffb8b8f7ffebbf75ea405/tokenizer.json
