Instructions to use hf-internal-testing/tiny-random-LayoutLMForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LayoutLMForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-LayoutLMForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LayoutLMForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-LayoutLMForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-LayoutLMForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 891 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-LayoutLMForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-LayoutLMForTokenClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-LayoutLMForTokenClassification/resolve/refs%2Fpr%2F1/model.safetensors
891 kB
- Xet hash:
- d835bbefbfd6fa3651478bd70637d8adc67c74b5ec1dcd49a60316d4a9f68185
- Size of remote file:
- 891 kB
- SHA256:
- aee8640dedf75decc8e5320dffc20ad817888d879306072acaf9b8ee8269b157
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