Instructions to use hf-tiny-model-private/tiny-random-LayoutLMForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-LayoutLMForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-LayoutLMForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-LayoutLMForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-LayoutLMForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-LayoutLMForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 891 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-LayoutLMForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-LayoutLMForSequenceClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-LayoutLMForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
891 kB
- Xet hash:
- ad2f8bb78620b71a7141054fd2fcc97e3dfa0204888447522408c4041deca556
- Size of remote file:
- 891 kB
- SHA256:
- 7c0ab29f88a4eb743e168d6a41acdb935eba61f6b25b9d8be8c33ab7326ad26c
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