Instructions to use hf-internal-testing/tiny-random-LayoutLMForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LayoutLMForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-LayoutLMForMaskedLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LayoutLMForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-LayoutLMForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-LayoutLMForMaskedLM: direct link, hf CLI and curl.
- Browser
- Download file 900 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-LayoutLMForMaskedLM/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-LayoutLMForMaskedLM@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-LayoutLMForMaskedLM/resolve/refs%2Fpr%2F1/model.safetensors
900 kB
- Xet hash:
- 3cb861f4249f8d1dc1c824b77d302c69525a130b1ed39776db9c3102901585b5
- Size of remote file:
- 900 kB
- SHA256:
- 0450cde18a413d4d04b5b89a401a976ae0a4e22854e3d98ca548613f47a7cc72
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.