Instructions to use hf-tiny-model-private/tiny-random-RemBertForTokenClassification 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-RemBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-RemBertForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RemBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-RemBertForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-RemBertForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 18.2 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-RemBertForTokenClassification/resolve/de52fbaf9078b85199ae0a834dfc5f4709c8aae5/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-RemBertForTokenClassification@de52fbaf9078b85199ae0a834dfc5f4709c8aae5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-RemBertForTokenClassification/resolve/de52fbaf9078b85199ae0a834dfc5f4709c8aae5/pytorch_model.bin
18.2 MB
- Xet hash:
- a2ede0b5c047bb97b2d6a64012289848fd3b88624f270bbd7877ca8e1d6512d5
- Size of remote file:
- 18.2 MB
- SHA256:
- c2b2dfcaba2da5aa2dbc76dbf793a39c67cb8ef592748b57496be954eeeb937e
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